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What is a Research Hypothesis: How to Write it, Types, and Examples
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Any research begins with a research question and a research hypothesis . A research question alone may not suffice to design the experiment(s) needed to answer it. A hypothesis is central to the scientific method. But what is a hypothesis ? A hypothesis is a testable statement that proposes a possible explanation to a phenomenon, and it may include a prediction. Next, you may ask what is a research hypothesis ? Simply put, a research hypothesis is a prediction or educated guess about the relationship between the variables that you want to investigate.
It is important to be thorough when developing your research hypothesis. Shortcomings in the framing of a hypothesis can affect the study design and the results. A better understanding of the research hypothesis definition and characteristics of a good hypothesis will make it easier for you to develop your own hypothesis for your research. Let’s dive in to know more about the types of research hypothesis , how to write a research hypothesis , and some research hypothesis examples .
Table of Contents
What is a hypothesis ?
A hypothesis is based on the existing body of knowledge in a study area. Framed before the data are collected, a hypothesis states the tentative relationship between independent and dependent variables, along with a prediction of the outcome.
What is a research hypothesis ?
Young researchers starting out their journey are usually brimming with questions like “ What is a hypothesis ?” “ What is a research hypothesis ?” “How can I write a good research hypothesis ?”
A research hypothesis is a statement that proposes a possible explanation for an observable phenomenon or pattern. It guides the direction of a study and predicts the outcome of the investigation. A research hypothesis is testable, i.e., it can be supported or disproven through experimentation or observation.
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Characteristics of a good hypothesis
Here are the characteristics of a good hypothesis :
- Clearly formulated and free of language errors and ambiguity
- Concise and not unnecessarily verbose
- Has clearly defined variables
- Testable and stated in a way that allows for it to be disproven
- Can be tested using a research design that is feasible, ethical, and practical
- Specific and relevant to the research problem
- Rooted in a thorough literature search
- Can generate new knowledge or understanding.
How to create an effective research hypothesis
A study begins with the formulation of a research question. A researcher then performs background research. This background information forms the basis for building a good research hypothesis . The researcher then performs experiments, collects, and analyzes the data, interprets the findings, and ultimately, determines if the findings support or negate the original hypothesis.
Let’s look at each step for creating an effective, testable, and good research hypothesis :
- Identify a research problem or question: Start by identifying a specific research problem.
- Review the literature: Conduct an in-depth review of the existing literature related to the research problem to grasp the current knowledge and gaps in the field.
- Formulate a clear and testable hypothesis : Based on the research question, use existing knowledge to form a clear and testable hypothesis . The hypothesis should state a predicted relationship between two or more variables that can be measured and manipulated. Improve the original draft till it is clear and meaningful.
- State the null hypothesis: The null hypothesis is a statement that there is no relationship between the variables you are studying.
- Define the population and sample: Clearly define the population you are studying and the sample you will be using for your research.
- Select appropriate methods for testing the hypothesis: Select appropriate research methods, such as experiments, surveys, or observational studies, which will allow you to test your research hypothesis .
Remember that creating a research hypothesis is an iterative process, i.e., you might have to revise it based on the data you collect. You may need to test and reject several hypotheses before answering the research problem.
How to write a research hypothesis
When you start writing a research hypothesis , you use an “if–then” statement format, which states the predicted relationship between two or more variables. Clearly identify the independent variables (the variables being changed) and the dependent variables (the variables being measured), as well as the population you are studying. Review and revise your hypothesis as needed.
An example of a research hypothesis in this format is as follows:
“ If [athletes] follow [cold water showers daily], then their [endurance] increases.”
Population: athletes
Independent variable: daily cold water showers
Dependent variable: endurance
You may have understood the characteristics of a good hypothesis . But note that a research hypothesis is not always confirmed; a researcher should be prepared to accept or reject the hypothesis based on the study findings.
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Research hypothesis checklist
Following from above, here is a 10-point checklist for a good research hypothesis :
- Testable: A research hypothesis should be able to be tested via experimentation or observation.
- Specific: A research hypothesis should clearly state the relationship between the variables being studied.
- Based on prior research: A research hypothesis should be based on existing knowledge and previous research in the field.
- Falsifiable: A research hypothesis should be able to be disproven through testing.
- Clear and concise: A research hypothesis should be stated in a clear and concise manner.
- Logical: A research hypothesis should be logical and consistent with current understanding of the subject.
- Relevant: A research hypothesis should be relevant to the research question and objectives.
- Feasible: A research hypothesis should be feasible to test within the scope of the study.
- Reflects the population: A research hypothesis should consider the population or sample being studied.
- Uncomplicated: A good research hypothesis is written in a way that is easy for the target audience to understand.
By following this research hypothesis checklist , you will be able to create a research hypothesis that is strong, well-constructed, and more likely to yield meaningful results.
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Types of research hypothesis
Different types of research hypothesis are used in scientific research:
1. Null hypothesis:
A null hypothesis states that there is no change in the dependent variable due to changes to the independent variable. This means that the results are due to chance and are not significant. A null hypothesis is denoted as H0 and is stated as the opposite of what the alternative hypothesis states.
Example: “ The newly identified virus is not zoonotic .”
2. Alternative hypothesis:
This states that there is a significant difference or relationship between the variables being studied. It is denoted as H1 or Ha and is usually accepted or rejected in favor of the null hypothesis.
Example: “ The newly identified virus is zoonotic .”
3. Directional hypothesis :
This specifies the direction of the relationship or difference between variables; therefore, it tends to use terms like increase, decrease, positive, negative, more, or less.
Example: “ The inclusion of intervention X decreases infant mortality compared to the original treatment .”
4. Non-directional hypothesis:
While it does not predict the exact direction or nature of the relationship between the two variables, a non-directional hypothesis states the existence of a relationship or difference between variables but not the direction, nature, or magnitude of the relationship. A non-directional hypothesis may be used when there is no underlying theory or when findings contradict previous research.
Example, “ Cats and dogs differ in the amount of affection they express .”
5. Simple hypothesis :
A simple hypothesis only predicts the relationship between one independent and another independent variable.
Example: “ Applying sunscreen every day slows skin aging .”
6 . Complex hypothesis :
A complex hypothesis states the relationship or difference between two or more independent and dependent variables.
Example: “ Applying sunscreen every day slows skin aging, reduces sun burn, and reduces the chances of skin cancer .” (Here, the three dependent variables are slowing skin aging, reducing sun burn, and reducing the chances of skin cancer.)
7. Associative hypothesis:
An associative hypothesis states that a change in one variable results in the change of the other variable. The associative hypothesis defines interdependency between variables.
Example: “ There is a positive association between physical activity levels and overall health .”
8 . Causal hypothesis:
A causal hypothesis proposes a cause-and-effect interaction between variables.
Example: “ Long-term alcohol use causes liver damage .”
Note that some of the types of research hypothesis mentioned above might overlap. The types of hypothesis chosen will depend on the research question and the objective of the study.
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Research hypothesis examples
Here are some good research hypothesis examples :
“The use of a specific type of therapy will lead to a reduction in symptoms of depression in individuals with a history of major depressive disorder.”
“Providing educational interventions on healthy eating habits will result in weight loss in overweight individuals.”
“Plants that are exposed to certain types of music will grow taller than those that are not exposed to music.”
“The use of the plant growth regulator X will lead to an increase in the number of flowers produced by plants.”
Characteristics that make a research hypothesis weak are unclear variables, unoriginality, being too general or too vague, and being untestable. A weak hypothesis leads to weak research and improper methods.
Some bad research hypothesis examples (and the reasons why they are “bad”) are as follows:
“This study will show that treatment X is better than any other treatment . ” (This statement is not testable, too broad, and does not consider other treatments that may be effective.)
“This study will prove that this type of therapy is effective for all mental disorders . ” (This statement is too broad and not testable as mental disorders are complex and different disorders may respond differently to different types of therapy.)
“Plants can communicate with each other through telepathy . ” (This statement is not testable and lacks a scientific basis.)
Importance of testable hypothesis
If a research hypothesis is not testable, the results will not prove or disprove anything meaningful. The conclusions will be vague at best. A testable hypothesis helps a researcher focus on the study outcome and understand the implication of the question and the different variables involved. A testable hypothesis helps a researcher make precise predictions based on prior research.
To be considered testable, there must be a way to prove that the hypothesis is true or false; further, the results of the hypothesis must be reproducible.
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Frequently Asked Questions (FAQs) on research hypothesis
1. What is the difference between research question and research hypothesis ?
A research question defines the problem and helps outline the study objective(s). It is an open-ended statement that is exploratory or probing in nature. Therefore, it does not make predictions or assumptions. It helps a researcher identify what information to collect. A research hypothesis , however, is a specific, testable prediction about the relationship between variables. Accordingly, it guides the study design and data analysis approach.
2. When to reject null hypothesis ?
A null hypothesis should be rejected when the evidence from a statistical test shows that it is unlikely to be true. This happens when the test statistic (e.g., p -value) is less than the defined significance level (e.g., 0.05). Rejecting the null hypothesis does not necessarily mean that the alternative hypothesis is true; it simply means that the evidence found is not compatible with the null hypothesis.
3. How can I be sure my hypothesis is testable?
A testable hypothesis should be specific and measurable, and it should state a clear relationship between variables that can be tested with data. To ensure that your hypothesis is testable, consider the following:
- Clearly define the key variables in your hypothesis. You should be able to measure and manipulate these variables in a way that allows you to test the hypothesis.
- The hypothesis should predict a specific outcome or relationship between variables that can be measured or quantified.
- You should be able to collect the necessary data within the constraints of your study.
- It should be possible for other researchers to replicate your study, using the same methods and variables.
- Your hypothesis should be testable by using appropriate statistical analysis techniques, so you can draw conclusions, and make inferences about the population from the sample data.
- The hypothesis should be able to be disproven or rejected through the collection of data.
4. How do I revise my research hypothesis if my data does not support it?
If your data does not support your research hypothesis , you will need to revise it or develop a new one. You should examine your data carefully and identify any patterns or anomalies, re-examine your research question, and/or revisit your theory to look for any alternative explanations for your results. Based on your review of the data, literature, and theories, modify your research hypothesis to better align it with the results you obtained. Use your revised hypothesis to guide your research design and data collection. It is important to remain objective throughout the process.
5. I am performing exploratory research. Do I need to formulate a research hypothesis?
As opposed to “confirmatory” research, where a researcher has some idea about the relationship between the variables under investigation, exploratory research (or hypothesis-generating research) looks into a completely new topic about which limited information is available. Therefore, the researcher will not have any prior hypotheses. In such cases, a researcher will need to develop a post-hoc hypothesis. A post-hoc research hypothesis is generated after these results are known.
6. How is a research hypothesis different from a research question?
A research question is an inquiry about a specific topic or phenomenon, typically expressed as a question. It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis.
7. Can a research hypothesis change during the research process?
Yes, research hypotheses can change during the research process. As researchers collect and analyze data, new insights and information may emerge that require modification or refinement of the initial hypotheses. This can be due to unexpected findings, limitations in the original hypotheses, or the need to explore additional dimensions of the research topic. Flexibility is crucial in research, allowing for adaptation and adjustment of hypotheses to align with the evolving understanding of the subject matter.
8. How many hypotheses should be included in a research study?
The number of research hypotheses in a research study varies depending on the nature and scope of the research. It is not necessary to have multiple hypotheses in every study. Some studies may have only one primary hypothesis, while others may have several related hypotheses. The number of hypotheses should be determined based on the research objectives, research questions, and the complexity of the research topic. It is important to ensure that the hypotheses are focused, testable, and directly related to the research aims.
9. Can research hypotheses be used in qualitative research?
Yes, research hypotheses can be used in qualitative research, although they are more commonly associated with quantitative research. In qualitative research, hypotheses may be formulated as tentative or exploratory statements that guide the investigation. Instead of testing hypotheses through statistical analysis, qualitative researchers may use the hypotheses to guide data collection and analysis, seeking to uncover patterns, themes, or relationships within the qualitative data. The emphasis in qualitative research is often on generating insights and understanding rather than confirming or rejecting specific research hypotheses through statistical testing.
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The Craft of Writing a Strong Hypothesis
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Table of Contents
Writing a hypothesis is one of the essential elements of a scientific research paper. It needs to be to the point, clearly communicating what your research is trying to accomplish. A blurry, drawn-out, or complexly-structured hypothesis can confuse your readers. Or worse, the editor and peer reviewers.
A captivating hypothesis is not too intricate. This blog will take you through the process so that, by the end of it, you have a better idea of how to convey your research paper's intent in just one sentence.
What is a Hypothesis?
The first step in your scientific endeavor, a hypothesis, is a strong, concise statement that forms the basis of your research. It is not the same as a thesis statement , which is a brief summary of your research paper .
The sole purpose of a hypothesis is to predict your paper's findings, data, and conclusion. It comes from a place of curiosity and intuition . When you write a hypothesis, you're essentially making an educated guess based on scientific prejudices and evidence, which is further proven or disproven through the scientific method.
The reason for undertaking research is to observe a specific phenomenon. A hypothesis, therefore, lays out what the said phenomenon is. And it does so through two variables, an independent and dependent variable.
The independent variable is the cause behind the observation, while the dependent variable is the effect of the cause. A good example of this is “mixing red and blue forms purple.” In this hypothesis, mixing red and blue is the independent variable as you're combining the two colors at your own will. The formation of purple is the dependent variable as, in this case, it is conditional to the independent variable.
Different Types of Hypotheses
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Types of hypotheses
Some would stand by the notion that there are only two types of hypotheses: a Null hypothesis and an Alternative hypothesis. While that may have some truth to it, it would be better to fully distinguish the most common forms as these terms come up so often, which might leave you out of context.
Apart from Null and Alternative, there are Complex, Simple, Directional, Non-Directional, Statistical, and Associative and casual hypotheses. They don't necessarily have to be exclusive, as one hypothesis can tick many boxes, but knowing the distinctions between them will make it easier for you to construct your own.
1. Null hypothesis
A null hypothesis proposes no relationship between two variables. Denoted by H 0 , it is a negative statement like “Attending physiotherapy sessions does not affect athletes' on-field performance.” Here, the author claims physiotherapy sessions have no effect on on-field performances. Even if there is, it's only a coincidence.
2. Alternative hypothesis
Considered to be the opposite of a null hypothesis, an alternative hypothesis is donated as H1 or Ha. It explicitly states that the dependent variable affects the independent variable. A good alternative hypothesis example is “Attending physiotherapy sessions improves athletes' on-field performance.” or “Water evaporates at 100 °C. ” The alternative hypothesis further branches into directional and non-directional.
- Directional hypothesis: A hypothesis that states the result would be either positive or negative is called directional hypothesis. It accompanies H1 with either the ‘<' or ‘>' sign.
- Non-directional hypothesis: A non-directional hypothesis only claims an effect on the dependent variable. It does not clarify whether the result would be positive or negative. The sign for a non-directional hypothesis is ‘≠.'
3. Simple hypothesis
A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, “Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking.
4. Complex hypothesis
In contrast to a simple hypothesis, a complex hypothesis implies the relationship between multiple independent and dependent variables. For instance, “Individuals who eat more fruits tend to have higher immunity, lesser cholesterol, and high metabolism.” The independent variable is eating more fruits, while the dependent variables are higher immunity, lesser cholesterol, and high metabolism.
5. Associative and casual hypothesis
Associative and casual hypotheses don't exhibit how many variables there will be. They define the relationship between the variables. In an associative hypothesis, changing any one variable, dependent or independent, affects others. In a casual hypothesis, the independent variable directly affects the dependent.
6. Empirical hypothesis
Also referred to as the working hypothesis, an empirical hypothesis claims a theory's validation via experiments and observation. This way, the statement appears justifiable and different from a wild guess.
Say, the hypothesis is “Women who take iron tablets face a lesser risk of anemia than those who take vitamin B12.” This is an example of an empirical hypothesis where the researcher the statement after assessing a group of women who take iron tablets and charting the findings.
7. Statistical hypothesis
The point of a statistical hypothesis is to test an already existing hypothesis by studying a population sample. Hypothesis like “44% of the Indian population belong in the age group of 22-27.” leverage evidence to prove or disprove a particular statement.
Characteristics of a Good Hypothesis
Writing a hypothesis is essential as it can make or break your research for you. That includes your chances of getting published in a journal. So when you're designing one, keep an eye out for these pointers:
- A research hypothesis has to be simple yet clear to look justifiable enough.
- It has to be testable — your research would be rendered pointless if too far-fetched into reality or limited by technology.
- It has to be precise about the results —what you are trying to do and achieve through it should come out in your hypothesis.
- A research hypothesis should be self-explanatory, leaving no doubt in the reader's mind.
- If you are developing a relational hypothesis, you need to include the variables and establish an appropriate relationship among them.
- A hypothesis must keep and reflect the scope for further investigations and experiments.
Separating a Hypothesis from a Prediction
Outside of academia, hypothesis and prediction are often used interchangeably. In research writing, this is not only confusing but also incorrect. And although a hypothesis and prediction are guesses at their core, there are many differences between them.
A hypothesis is an educated guess or even a testable prediction validated through research. It aims to analyze the gathered evidence and facts to define a relationship between variables and put forth a logical explanation behind the nature of events.
Predictions are assumptions or expected outcomes made without any backing evidence. They are more fictionally inclined regardless of where they originate from.
For this reason, a hypothesis holds much more weight than a prediction. It sticks to the scientific method rather than pure guesswork. "Planets revolve around the Sun." is an example of a hypothesis as it is previous knowledge and observed trends. Additionally, we can test it through the scientific method.
Whereas "COVID-19 will be eradicated by 2030." is a prediction. Even though it results from past trends, we can't prove or disprove it. So, the only way this gets validated is to wait and watch if COVID-19 cases end by 2030.
Finally, How to Write a Hypothesis
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Quick tips on writing a hypothesis
1. Be clear about your research question
A hypothesis should instantly address the research question or the problem statement. To do so, you need to ask a question. Understand the constraints of your undertaken research topic and then formulate a simple and topic-centric problem. Only after that can you develop a hypothesis and further test for evidence.
2. Carry out a recce
Once you have your research's foundation laid out, it would be best to conduct preliminary research. Go through previous theories, academic papers, data, and experiments before you start curating your research hypothesis. It will give you an idea of your hypothesis's viability or originality.
Making use of references from relevant research papers helps draft a good research hypothesis. SciSpace Discover offers a repository of over 270 million research papers to browse through and gain a deeper understanding of related studies on a particular topic. Additionally, you can use SciSpace Copilot , your AI research assistant, for reading any lengthy research paper and getting a more summarized context of it. A hypothesis can be formed after evaluating many such summarized research papers. Copilot also offers explanations for theories and equations, explains paper in simplified version, allows you to highlight any text in the paper or clip math equations and tables and provides a deeper, clear understanding of what is being said. This can improve the hypothesis by helping you identify potential research gaps.
3. Create a 3-dimensional hypothesis
Variables are an essential part of any reasonable hypothesis. So, identify your independent and dependent variable(s) and form a correlation between them. The ideal way to do this is to write the hypothetical assumption in the ‘if-then' form. If you use this form, make sure that you state the predefined relationship between the variables.
In another way, you can choose to present your hypothesis as a comparison between two variables. Here, you must specify the difference you expect to observe in the results.
4. Write the first draft
Now that everything is in place, it's time to write your hypothesis. For starters, create the first draft. In this version, write what you expect to find from your research.
Clearly separate your independent and dependent variables and the link between them. Don't fixate on syntax at this stage. The goal is to ensure your hypothesis addresses the issue.
5. Proof your hypothesis
After preparing the first draft of your hypothesis, you need to inspect it thoroughly. It should tick all the boxes, like being concise, straightforward, relevant, and accurate. Your final hypothesis has to be well-structured as well.
Research projects are an exciting and crucial part of being a scholar. And once you have your research question, you need a great hypothesis to begin conducting research. Thus, knowing how to write a hypothesis is very important.
Now that you have a firmer grasp on what a good hypothesis constitutes, the different kinds there are, and what process to follow, you will find it much easier to write your hypothesis, which ultimately helps your research.
Now it's easier than ever to streamline your research workflow with SciSpace Discover . Its integrated, comprehensive end-to-end platform for research allows scholars to easily discover, write and publish their research and fosters collaboration.
It includes everything you need, including a repository of over 270 million research papers across disciplines, SEO-optimized summaries and public profiles to show your expertise and experience.
If you found these tips on writing a research hypothesis useful, head over to our blog on Statistical Hypothesis Testing to learn about the top researchers, papers, and institutions in this domain.
Frequently Asked Questions (FAQs)
1. what is the definition of hypothesis.
According to the Oxford dictionary, a hypothesis is defined as “An idea or explanation of something that is based on a few known facts, but that has not yet been proved to be true or correct”.
2. What is an example of hypothesis?
The hypothesis is a statement that proposes a relationship between two or more variables. An example: "If we increase the number of new users who join our platform by 25%, then we will see an increase in revenue."
3. What is an example of null hypothesis?
A null hypothesis is a statement that there is no relationship between two variables. The null hypothesis is written as H0. The null hypothesis states that there is no effect. For example, if you're studying whether or not a particular type of exercise increases strength, your null hypothesis will be "there is no difference in strength between people who exercise and people who don't."
4. What are the types of research?
• Fundamental research
• Applied research
• Qualitative research
• Quantitative research
• Mixed research
• Exploratory research
• Longitudinal research
• Cross-sectional research
• Field research
• Laboratory research
• Fixed research
• Flexible research
• Action research
• Policy research
• Classification research
• Comparative research
• Causal research
• Inductive research
• Deductive research
5. How to write a hypothesis?
• Your hypothesis should be able to predict the relationship and outcome.
• Avoid wordiness by keeping it simple and brief.
• Your hypothesis should contain observable and testable outcomes.
• Your hypothesis should be relevant to the research question.
6. What are the 2 types of hypothesis?
• Null hypotheses are used to test the claim that "there is no difference between two groups of data".
• Alternative hypotheses test the claim that "there is a difference between two data groups".
7. Difference between research question and research hypothesis?
A research question is a broad, open-ended question you will try to answer through your research. A hypothesis is a statement based on prior research or theory that you expect to be true due to your study. Example - Research question: What are the factors that influence the adoption of the new technology? Research hypothesis: There is a positive relationship between age, education and income level with the adoption of the new technology.
8. What is plural for hypothesis?
The plural of hypothesis is hypotheses. Here's an example of how it would be used in a statement, "Numerous well-considered hypotheses are presented in this part, and they are supported by tables and figures that are well-illustrated."
9. What is the red queen hypothesis?
The red queen hypothesis in evolutionary biology states that species must constantly evolve to avoid extinction because if they don't, they will be outcompeted by other species that are evolving. Leigh Van Valen first proposed it in 1973; since then, it has been tested and substantiated many times.
10. Who is known as the father of null hypothesis?
The father of the null hypothesis is Sir Ronald Fisher. He published a paper in 1925 that introduced the concept of null hypothesis testing, and he was also the first to use the term itself.
11. When to reject null hypothesis?
You need to find a significant difference between your two populations to reject the null hypothesis. You can determine that by running statistical tests such as an independent sample t-test or a dependent sample t-test. You should reject the null hypothesis if the p-value is less than 0.05.
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How Do You Write a Hypothesis for a Research Paper: Tips and Examples
Crafting a well-defined hypothesis is a critical step in the research process, serving as the foundation for your study. A hypothesis not only guides your research design but also provides a clear focus for your investigation. In this article, we will explore the essential aspects of writing a strong hypothesis for a research paper, including its characteristics, formulation steps, types, and common pitfalls to avoid. Additionally, we will provide examples from various disciplines to illustrate what makes a hypothesis effective.
Key Takeaways
- A hypothesis is a testable statement that predicts the relationship between variables in your research.
- Clarity and precision are crucial for a strong hypothesis, ensuring that it is understandable and specific.
- A good hypothesis must be testable and falsifiable, meaning it can be supported or refuted through experimentation or observation.
- Formulating a hypothesis involves identifying a research problem, conducting a literature review, and clearly stating the expected outcome.
- Avoid common pitfalls such as overly complex hypotheses, vague language, and lack of testability to ensure your hypothesis is effective.
Understanding the Role of a Hypothesis in Research
Defining a hypothesis.
A hypothesis is a testable prediction about the relationship between two or more variables. It serves as a navigational tool in the research process, directing what you aim to predict and how. Crafting a thesis statement is crucial in the writing process, guiding research and shaping arguments.
Purpose and Importance of a Hypothesis
In research, a hypothesis serves as the cornerstone for your empirical study. It not only lays out what you aim to investigate but also provides a structured approach for your data collection and analysis. Flexibility and clarity are key for effective statements.
Hypothesis vs. Prediction
A hypothesis is an attempt at explaining a phenomenon or the relationships between phenomena/variables in the real world. While hypotheses are sometimes called “educated guesses,” they should be based on previous observations, existing theories, scientific evidence, and logic. A hypothesis is not a prediction; rather, predictions are based on clearly formulated hypotheses.
Key Characteristics of a Strong Hypothesis
A robust hypothesis is essential for guiding your research effectively. Firstly, clarity and precision are paramount . Your hypothesis should be specific and unambiguous, providing a clear understanding of the expected relationship between variables. This ensures that your research question is well-defined and comprehensible.
Testability and falsifiability are also crucial. A hypothesis must be testable, allowing you to analyze data through empirical means, such as observation or experimentation, to assess if there is significant support for the hypothesis. Additionally, it should be falsifiable, meaning that it can be proven wrong through evidence.
Lastly, relevance to the research question is vital. Your hypothesis should be grounded in existing research or theoretical frameworks, ensuring its applicability and significance to the field of study. This connection to prior research not only strengthens your hypothesis but also aligns it with the broader academic discourse.
Steps to Formulate a Hypothesis for a Research Paper
Identifying the research problem.
The first step in formulating a hypothesis is to clearly identify the research problem. This involves understanding the phenomenon or the relationships between variables that you wish to explore. A well-defined research problem sets the stage for a focused and effective hypothesis.
Conducting a Literature Review
Before you can formulate a hypothesis, it's essential to conduct a thorough literature review. This helps you understand what has already been studied and where gaps in the research exist. By reviewing existing literature, you can ensure that your hypothesis is both original and relevant.
Formulating the Hypothesis
Once you have identified the research problem and reviewed the literature, you can begin to formulate your hypothesis . A strong hypothesis should be clear, testable, and directly related to the research question. It often helps to frame your hypothesis as an 'if-then' statement, which clearly outlines the expected relationship between variables.
Types of Hypotheses in Research
Understanding the various types of hypotheses is crucial for crafting effective research. Each type serves a unique purpose and can significantly influence the direction and outcomes of your study. All hypotheses contrast with the null hypothesis , which posits that no significant relationship exists between the variables under investigation.
Common Pitfalls to Avoid When Writing a Hypothesis
When crafting a hypothesis for your research paper, it's crucial to steer clear of common mistakes that can undermine your work. Avoiding these pitfalls will help you create a robust and testable hypothesis that can withstand academic scrutiny.
Examples of Well-Written Hypotheses
In this section, we will explore various examples of well-crafted hypotheses to help you understand what makes a hypothesis strong and effective. By examining these examples, you can gain insights into the essential components that contribute to a robust hypothesis.
Testing and Refining Your Hypothesis
Once you have formulated your hypothesis, the next crucial step is to test and refine it. This process ensures that your hypothesis is robust and reliable, ultimately contributing to the validity of your research findings.
Testing and refining your hypothesis is a crucial step in your thesis journey. It ensures that your research is on the right track and that your findings are valid. To make this process easier, our Thesis Action Plan offers a structured approach to help you navigate through each stage with confidence. Don't let uncertainty hold you back. Visit our website to learn more and claim your special offer now !
Crafting a well-defined hypothesis is a critical step in the research process, serving as the foundation upon which your entire study is built. A clear and concise hypothesis not only guides your research design and methodology but also provides a focal point for data collection and analysis. By following the tips and examples provided in this article, researchers can develop robust hypotheses that are both testable and meaningful. Remember, a strong hypothesis is characterized by its specificity, clarity, and relevance to the research question. As you embark on your research journey, take the time to refine your hypothesis, as it will significantly impact the quality and credibility of your study. With careful consideration and thoughtful formulation, your hypothesis can pave the way for insightful and impactful research findings.
Frequently Asked Questions
What is a hypothesis in a research paper.
A hypothesis in a research paper is a statement that predicts the relationship between variables. It serves as a tentative explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.
How do I formulate a strong hypothesis?
To formulate a strong hypothesis, ensure it is clear, precise, testable, and relevant to your research question. Conducting a thorough literature review can help you identify gaps in existing knowledge and formulate a hypothesis that addresses those gaps.
What is the difference between a hypothesis and a prediction?
A hypothesis is a testable statement about the relationship between two or more variables, while a prediction is a specific outcome that you expect to observe if the hypothesis is true. Predictions are often derived from hypotheses.
What are the types of hypotheses in research?
The main types of hypotheses in research are the null hypothesis, alternative hypothesis, directional hypothesis, and non-directional hypothesis. Each type serves a different purpose in statistical testing and research design.
Why is testability important in a hypothesis?
Testability is crucial in a hypothesis because it allows researchers to use empirical methods to determine whether the hypothesis is supported or refuted by the data. A hypothesis must be testable to be scientifically valid.
Can a hypothesis be revised?
Yes, a hypothesis can be revised based on new data, insights, or changes in the research focus. Revising a hypothesis is a common part of the scientific process as researchers refine their questions and methods.
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- How to Write a Strong Hypothesis | Guide & Examples
How to Write a Strong Hypothesis | Guide & Examples
Published on 6 May 2022 by Shona McCombes .
A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection.
Table of contents
What is a hypothesis, developing a hypothesis (with example), hypothesis examples, frequently asked questions about writing hypotheses.
A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.
A hypothesis is not just a guess – it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).
Variables in hypotheses
Hypotheses propose a relationship between two or more variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.
In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .
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Step 1: ask a question.
Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.
Step 2: Do some preliminary research
Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.
At this stage, you might construct a conceptual framework to identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise more complex constructs.
Step 3: Formulate your hypothesis
Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.
Step 4: Refine your hypothesis
You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:
- The relevant variables
- The specific group being studied
- The predicted outcome of the experiment or analysis
Step 5: Phrase your hypothesis in three ways
To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable.
In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.
If you are comparing two groups, the hypothesis can state what difference you expect to find between them.
Step 6. Write a null hypothesis
If your research involves statistical hypothesis testing , you will also have to write a null hypothesis. The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .
Research question | Hypothesis | Null hypothesis |
---|---|---|
What are the health benefits of eating an apple a day? | Increasing apple consumption in over-60s will result in decreasing frequency of doctor’s visits. | Increasing apple consumption in over-60s will have no effect on frequency of doctor’s visits. |
Which airlines have the most delays? | Low-cost airlines are more likely to have delays than premium airlines. | Low-cost and premium airlines are equally likely to have delays. |
Can flexible work arrangements improve job satisfaction? | Employees who have flexible working hours will report greater job satisfaction than employees who work fixed hours. | There is no relationship between working hour flexibility and job satisfaction. |
How effective is secondary school sex education at reducing teen pregnancies? | Teenagers who received sex education lessons throughout secondary school will have lower rates of unplanned pregnancy than teenagers who did not receive any sex education. | Secondary school sex education has no effect on teen pregnancy rates. |
What effect does daily use of social media have on the attention span of under-16s? | There is a negative correlation between time spent on social media and attention span in under-16s. | There is no relationship between social media use and attention span in under-16s. |
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).
A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).
A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.
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How to Develop a Good Research Hypothesis
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The story of a research study begins by asking a question. Researchers all around the globe are asking curious questions and formulating research hypothesis. However, whether the research study provides an effective conclusion depends on how well one develops a good research hypothesis. Research hypothesis examples could help researchers get an idea as to how to write a good research hypothesis.
This blog will help you understand what is a research hypothesis, its characteristics and, how to formulate a research hypothesis
Table of Contents
What is Hypothesis?
Hypothesis is an assumption or an idea proposed for the sake of argument so that it can be tested. It is a precise, testable statement of what the researchers predict will be outcome of the study. Hypothesis usually involves proposing a relationship between two variables: the independent variable (what the researchers change) and the dependent variable (what the research measures).
What is a Research Hypothesis?
Research hypothesis is a statement that introduces a research question and proposes an expected result. It is an integral part of the scientific method that forms the basis of scientific experiments. Therefore, you need to be careful and thorough when building your research hypothesis. A minor flaw in the construction of your hypothesis could have an adverse effect on your experiment. In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment).
Characteristics of a Good Research Hypothesis
As the hypothesis is specific, there is a testable prediction about what you expect to happen in a study. You may consider drawing hypothesis from previously published research based on the theory.
A good research hypothesis involves more effort than just a guess. In particular, your hypothesis may begin with a question that could be further explored through background research.
To help you formulate a promising research hypothesis, you should ask yourself the following questions:
- Is the language clear and focused?
- What is the relationship between your hypothesis and your research topic?
- Is your hypothesis testable? If yes, then how?
- What are the possible explanations that you might want to explore?
- Does your hypothesis include both an independent and dependent variable?
- Can you manipulate your variables without hampering the ethical standards?
- Does your research predict the relationship and outcome?
- Is your research simple and concise (avoids wordiness)?
- Is it clear with no ambiguity or assumptions about the readers’ knowledge
- Is your research observable and testable results?
- Is it relevant and specific to the research question or problem?
![how to create research hypothesis research hypothesis example](https://www.enago.com/academy/wp-content/uploads/2022/09/ResearchHypothesis.jpg)
The questions listed above can be used as a checklist to make sure your hypothesis is based on a solid foundation. Furthermore, it can help you identify weaknesses in your hypothesis and revise it if necessary.
Source: Educational Hub
How to formulate a research hypothesis.
A testable hypothesis is not a simple statement. It is rather an intricate statement that needs to offer a clear introduction to a scientific experiment, its intentions, and the possible outcomes. However, there are some important things to consider when building a compelling hypothesis.
1. State the problem that you are trying to solve.
Make sure that the hypothesis clearly defines the topic and the focus of the experiment.
2. Try to write the hypothesis as an if-then statement.
Follow this template: If a specific action is taken, then a certain outcome is expected.
3. Define the variables
Independent variables are the ones that are manipulated, controlled, or changed. Independent variables are isolated from other factors of the study.
Dependent variables , as the name suggests are dependent on other factors of the study. They are influenced by the change in independent variable.
4. Scrutinize the hypothesis
Evaluate assumptions, predictions, and evidence rigorously to refine your understanding.
Types of Research Hypothesis
The types of research hypothesis are stated below:
1. Simple Hypothesis
It predicts the relationship between a single dependent variable and a single independent variable.
2. Complex Hypothesis
It predicts the relationship between two or more independent and dependent variables.
3. Directional Hypothesis
It specifies the expected direction to be followed to determine the relationship between variables and is derived from theory. Furthermore, it implies the researcher’s intellectual commitment to a particular outcome.
4. Non-directional Hypothesis
It does not predict the exact direction or nature of the relationship between the two variables. The non-directional hypothesis is used when there is no theory involved or when findings contradict previous research.
5. Associative and Causal Hypothesis
The associative hypothesis defines interdependency between variables. A change in one variable results in the change of the other variable. On the other hand, the causal hypothesis proposes an effect on the dependent due to manipulation of the independent variable.
6. Null Hypothesis
Null hypothesis states a negative statement to support the researcher’s findings that there is no relationship between two variables. There will be no changes in the dependent variable due the manipulation of the independent variable. Furthermore, it states results are due to chance and are not significant in terms of supporting the idea being investigated.
7. Alternative Hypothesis
It states that there is a relationship between the two variables of the study and that the results are significant to the research topic. An experimental hypothesis predicts what changes will take place in the dependent variable when the independent variable is manipulated. Also, it states that the results are not due to chance and that they are significant in terms of supporting the theory being investigated.
Research Hypothesis Examples of Independent and Dependent Variables
Research Hypothesis Example 1 The greater number of coal plants in a region (independent variable) increases water pollution (dependent variable). If you change the independent variable (building more coal factories), it will change the dependent variable (amount of water pollution).
Research Hypothesis Example 2 What is the effect of diet or regular soda (independent variable) on blood sugar levels (dependent variable)? If you change the independent variable (the type of soda you consume), it will change the dependent variable (blood sugar levels)
You should not ignore the importance of the above steps. The validity of your experiment and its results rely on a robust testable hypothesis. Developing a strong testable hypothesis has few advantages, it compels us to think intensely and specifically about the outcomes of a study. Consequently, it enables us to understand the implication of the question and the different variables involved in the study. Furthermore, it helps us to make precise predictions based on prior research. Hence, forming a hypothesis would be of great value to the research. Here are some good examples of testable hypotheses.
More importantly, you need to build a robust testable research hypothesis for your scientific experiments. A testable hypothesis is a hypothesis that can be proved or disproved as a result of experimentation.
Importance of a Testable Hypothesis
To devise and perform an experiment using scientific method, you need to make sure that your hypothesis is testable. To be considered testable, some essential criteria must be met:
- There must be a possibility to prove that the hypothesis is true.
- There must be a possibility to prove that the hypothesis is false.
- The results of the hypothesis must be reproducible.
Without these criteria, the hypothesis and the results will be vague. As a result, the experiment will not prove or disprove anything significant.
What are your experiences with building hypotheses for scientific experiments? What challenges did you face? How did you overcome these challenges? Please share your thoughts with us in the comments section.
Frequently Asked Questions
The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a ‘if-then’ structure. 3. Defining the variables: Define the variables as Dependent or Independent based on their dependency to other factors. 4. Scrutinizing the hypothesis: Identify the type of your hypothesis
Hypothesis testing is a statistical tool which is used to make inferences about a population data to draw conclusions for a particular hypothesis.
Hypothesis in statistics is a formal statement about the nature of a population within a structured framework of a statistical model. It is used to test an existing hypothesis by studying a population.
Research hypothesis is a statement that introduces a research question and proposes an expected result. It forms the basis of scientific experiments.
The different types of hypothesis in research are: • Null hypothesis: Null hypothesis is a negative statement to support the researcher’s findings that there is no relationship between two variables. • Alternate hypothesis: Alternate hypothesis predicts the relationship between the two variables of the study. • Directional hypothesis: Directional hypothesis specifies the expected direction to be followed to determine the relationship between variables. • Non-directional hypothesis: Non-directional hypothesis does not predict the exact direction or nature of the relationship between the two variables. • Simple hypothesis: Simple hypothesis predicts the relationship between a single dependent variable and a single independent variable. • Complex hypothesis: Complex hypothesis predicts the relationship between two or more independent and dependent variables. • Associative and casual hypothesis: Associative and casual hypothesis predicts the relationship between two or more independent and dependent variables. • Empirical hypothesis: Empirical hypothesis can be tested via experiments and observation. • Statistical hypothesis: A statistical hypothesis utilizes statistical models to draw conclusions about broader populations.
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Wow! You really simplified your explanation that even dummies would find it easy to comprehend. Thank you so much.
Thanks a lot for your valuable guidance.
I enjoy reading the post. Hypotheses are actually an intrinsic part in a study. It bridges the research question and the methodology of the study.
Useful piece!
This is awesome.Wow.
It very interesting to read the topic, can you guide me any specific example of hypothesis process establish throw the Demand and supply of the specific product in market
Nicely explained
It is really a useful for me Kindly give some examples of hypothesis
It was a well explained content ,can you please give me an example with the null and alternative hypothesis illustrated
clear and concise. thanks.
So Good so Amazing
Good to learn
Thanks a lot for explaining to my level of understanding
Explained well and in simple terms. Quick read! Thank you
It awesome. It has really positioned me in my research project
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How to Write a Research Hypothesis: Good & Bad Examples
What is a research hypothesis?
A research hypothesis is an attempt at explaining a phenomenon or the relationships between phenomena/variables in the real world. Hypotheses are sometimes called “educated guesses”, but they are in fact (or let’s say they should be) based on previous observations, existing theories, scientific evidence, and logic. A research hypothesis is also not a prediction—rather, predictions are ( should be) based on clearly formulated hypotheses. For example, “We tested the hypothesis that KLF2 knockout mice would show deficiencies in heart development” is an assumption or prediction, not a hypothesis.
The research hypothesis at the basis of this prediction is “the product of the KLF2 gene is involved in the development of the cardiovascular system in mice”—and this hypothesis is probably (hopefully) based on a clear observation, such as that mice with low levels of Kruppel-like factor 2 (which KLF2 codes for) seem to have heart problems. From this hypothesis, you can derive the idea that a mouse in which this particular gene does not function cannot develop a normal cardiovascular system, and then make the prediction that we started with.
What is the difference between a hypothesis and a prediction?
You might think that these are very subtle differences, and you will certainly come across many publications that do not contain an actual hypothesis or do not make these distinctions correctly. But considering that the formulation and testing of hypotheses is an integral part of the scientific method, it is good to be aware of the concepts underlying this approach. The two hallmarks of a scientific hypothesis are falsifiability (an evaluation standard that was introduced by the philosopher of science Karl Popper in 1934) and testability —if you cannot use experiments or data to decide whether an idea is true or false, then it is not a hypothesis (or at least a very bad one).
So, in a nutshell, you (1) look at existing evidence/theories, (2) come up with a hypothesis, (3) make a prediction that allows you to (4) design an experiment or data analysis to test it, and (5) come to a conclusion. Of course, not all studies have hypotheses (there is also exploratory or hypothesis-generating research), and you do not necessarily have to state your hypothesis as such in your paper.
But for the sake of understanding the principles of the scientific method, let’s first take a closer look at the different types of hypotheses that research articles refer to and then give you a step-by-step guide for how to formulate a strong hypothesis for your own paper.
Types of Research Hypotheses
Hypotheses can be simple , which means they describe the relationship between one single independent variable (the one you observe variations in or plan to manipulate) and one single dependent variable (the one you expect to be affected by the variations/manipulation). If there are more variables on either side, you are dealing with a complex hypothesis. You can also distinguish hypotheses according to the kind of relationship between the variables you are interested in (e.g., causal or associative ). But apart from these variations, we are usually interested in what is called the “alternative hypothesis” and, in contrast to that, the “null hypothesis”. If you think these two should be listed the other way round, then you are right, logically speaking—the alternative should surely come second. However, since this is the hypothesis we (as researchers) are usually interested in, let’s start from there.
Alternative Hypothesis
If you predict a relationship between two variables in your study, then the research hypothesis that you formulate to describe that relationship is your alternative hypothesis (usually H1 in statistical terms). The goal of your hypothesis testing is thus to demonstrate that there is sufficient evidence that supports the alternative hypothesis, rather than evidence for the possibility that there is no such relationship. The alternative hypothesis is usually the research hypothesis of a study and is based on the literature, previous observations, and widely known theories.
Null Hypothesis
The hypothesis that describes the other possible outcome, that is, that your variables are not related, is the null hypothesis ( H0 ). Based on your findings, you choose between the two hypotheses—usually that means that if your prediction was correct, you reject the null hypothesis and accept the alternative. Make sure, however, that you are not getting lost at this step of the thinking process: If your prediction is that there will be no difference or change, then you are trying to find support for the null hypothesis and reject H1.
Directional Hypothesis
While the null hypothesis is obviously “static”, the alternative hypothesis can specify a direction for the observed relationship between variables—for example, that mice with higher expression levels of a certain protein are more active than those with lower levels. This is then called a one-tailed hypothesis.
Another example for a directional one-tailed alternative hypothesis would be that
H1: Attending private classes before important exams has a positive effect on performance.
Your null hypothesis would then be that
H0: Attending private classes before important exams has no/a negative effect on performance.
Nondirectional Hypothesis
A nondirectional hypothesis does not specify the direction of the potentially observed effect, only that there is a relationship between the studied variables—this is called a two-tailed hypothesis. For instance, if you are studying a new drug that has shown some effects on pathways involved in a certain condition (e.g., anxiety) in vitro in the lab, but you can’t say for sure whether it will have the same effects in an animal model or maybe induce other/side effects that you can’t predict and potentially increase anxiety levels instead, you could state the two hypotheses like this:
H1: The only lab-tested drug (somehow) affects anxiety levels in an anxiety mouse model.
You then test this nondirectional alternative hypothesis against the null hypothesis:
H0: The only lab-tested drug has no effect on anxiety levels in an anxiety mouse model.
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How to Write a Hypothesis for a Research Paper
Now that we understand the important distinctions between different kinds of research hypotheses, let’s look at a simple process of how to write a hypothesis.
Writing a Hypothesis Step:1
Ask a question, based on earlier research. Research always starts with a question, but one that takes into account what is already known about a topic or phenomenon. For example, if you are interested in whether people who have pets are happier than those who don’t, do a literature search and find out what has already been demonstrated. You will probably realize that yes, there is quite a bit of research that shows a relationship between happiness and owning a pet—and even studies that show that owning a dog is more beneficial than owning a cat ! Let’s say you are so intrigued by this finding that you wonder:
What is it that makes dog owners even happier than cat owners?
Let’s move on to Step 2 and find an answer to that question.
Writing a Hypothesis Step 2:
Formulate a strong hypothesis by answering your own question. Again, you don’t want to make things up, take unicorns into account, or repeat/ignore what has already been done. Looking at the dog-vs-cat papers your literature search returned, you see that most studies are based on self-report questionnaires on personality traits, mental health, and life satisfaction. What you don’t find is any data on actual (mental or physical) health measures, and no experiments. You therefore decide to make a bold claim come up with the carefully thought-through hypothesis that it’s maybe the lifestyle of the dog owners, which includes walking their dog several times per day, engaging in fun and healthy activities such as agility competitions, and taking them on trips, that gives them that extra boost in happiness. You could therefore answer your question in the following way:
Dog owners are happier than cat owners because of the dog-related activities they engage in.
Now you have to verify that your hypothesis fulfills the two requirements we introduced at the beginning of this resource article: falsifiability and testability . If it can’t be wrong and can’t be tested, it’s not a hypothesis. We are lucky, however, because yes, we can test whether owning a dog but not engaging in any of those activities leads to lower levels of happiness or well-being than owning a dog and playing and running around with them or taking them on trips.
Writing a Hypothesis Step 3:
Make your predictions and define your variables. We have verified that we can test our hypothesis, but now we have to define all the relevant variables, design our experiment or data analysis, and make precise predictions. You could, for example, decide to study dog owners (not surprising at this point), let them fill in questionnaires about their lifestyle as well as their life satisfaction (as other studies did), and then compare two groups of active and inactive dog owners. Alternatively, if you want to go beyond the data that earlier studies produced and analyzed and directly manipulate the activity level of your dog owners to study the effect of that manipulation, you could invite them to your lab, select groups of participants with similar lifestyles, make them change their lifestyle (e.g., couch potato dog owners start agility classes, very active ones have to refrain from any fun activities for a certain period of time) and assess their happiness levels before and after the intervention. In both cases, your independent variable would be “ level of engagement in fun activities with dog” and your dependent variable would be happiness or well-being .
Examples of a Good and Bad Hypothesis
Let’s look at a few examples of good and bad hypotheses to get you started.
Good Hypothesis Examples
Working from home improves job satisfaction. | Employees who are allowed to work from home are less likely to quit within 2 years than those who need to come to the office. |
Sleep deprivation affects cognition. | Students who sleep <5 hours/night don’t perform as well on exams as those who sleep >7 hours/night. |
Animals adapt to their environment. | Birds of the same species living on different islands have differently shaped beaks depending on the available food source. |
Social media use causes anxiety. | Do teenagers who refrain from using social media for 4 weeks show improvements in anxiety symptoms? |
Bad Hypothesis Examples
Garlic repels vampires. | Participants who eat garlic daily will not be harmed by vampires. | Nobody gets harmed by vampires— . |
Chocolate is better than vanilla. | No clearly defined variables— . |
Tips for Writing a Research Hypothesis
If you understood the distinction between a hypothesis and a prediction we made at the beginning of this article, then you will have no problem formulating your hypotheses and predictions correctly. To refresh your memory: We have to (1) look at existing evidence, (2) come up with a hypothesis, (3) make a prediction, and (4) design an experiment. For example, you could summarize your dog/happiness study like this:
(1) While research suggests that dog owners are happier than cat owners, there are no reports on what factors drive this difference. (2) We hypothesized that it is the fun activities that many dog owners (but very few cat owners) engage in with their pets that increases their happiness levels. (3) We thus predicted that preventing very active dog owners from engaging in such activities for some time and making very inactive dog owners take up such activities would lead to an increase and decrease in their overall self-ratings of happiness, respectively. (4) To test this, we invited dog owners into our lab, assessed their mental and emotional well-being through questionnaires, and then assigned them to an “active” and an “inactive” group, depending on…
Note that you use “we hypothesize” only for your hypothesis, not for your experimental prediction, and “would” or “if – then” only for your prediction, not your hypothesis. A hypothesis that states that something “would” affect something else sounds as if you don’t have enough confidence to make a clear statement—in which case you can’t expect your readers to believe in your research either. Write in the present tense, don’t use modal verbs that express varying degrees of certainty (such as may, might, or could ), and remember that you are not drawing a conclusion while trying not to exaggerate but making a clear statement that you then, in a way, try to disprove . And if that happens, that is not something to fear but an important part of the scientific process.
Similarly, don’t use “we hypothesize” when you explain the implications of your research or make predictions in the conclusion section of your manuscript, since these are clearly not hypotheses in the true sense of the word. As we said earlier, you will find that many authors of academic articles do not seem to care too much about these rather subtle distinctions, but thinking very clearly about your own research will not only help you write better but also ensure that even that infamous Reviewer 2 will find fewer reasons to nitpick about your manuscript.
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On the Wordvice academic resources website , you can also find many more articles and other resources that can help you with writing the other parts of your research paper , with making a research paper outline before you put everything together, or with writing an effective cover letter once you are ready to submit.
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How to Write a Hypothesis: A Step-by-Step Guide
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Introduction
An overview of the research hypothesis, different types of hypotheses, variables in a hypothesis, how to formulate an effective research hypothesis, designing a study around your hypothesis.
The scientific method can derive and test predictions as hypotheses. Empirical research can then provide support (or lack thereof) for the hypotheses. Even failure to find support for a hypothesis still represents a valuable contribution to scientific knowledge. Let's look more closely at the idea of the hypothesis and the role it plays in research.
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As much as the term exists in everyday language, there is a detailed development that informs the word "hypothesis" when applied to research. A good research hypothesis is informed by prior research and guides research design and data analysis , so it is important to understand how a hypothesis is defined and understood by researchers.
What is the simple definition of a hypothesis?
A hypothesis is a testable prediction about an outcome between two or more variables . It functions as a navigational tool in the research process, directing what you aim to predict and how.
What is the hypothesis for in research?
In research, a hypothesis serves as the cornerstone for your empirical study. It not only lays out what you aim to investigate but also provides a structured approach for your data collection and analysis.
Essentially, it bridges the gap between the theoretical and the empirical, guiding your investigation throughout its course.
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What is an example of a hypothesis?
If you are studying the relationship between physical exercise and mental health, a suitable hypothesis could be: "Regular physical exercise leads to improved mental well-being among adults."
This statement constitutes a specific and testable hypothesis that directly relates to the variables you are investigating.
What makes a good hypothesis?
A good hypothesis possesses several key characteristics. Firstly, it must be testable, allowing you to analyze data through empirical means, such as observation or experimentation, to assess if there is significant support for the hypothesis. Secondly, a hypothesis should be specific and unambiguous, giving a clear understanding of the expected relationship between variables. Lastly, it should be grounded in existing research or theoretical frameworks , ensuring its relevance and applicability.
Understanding the types of hypotheses can greatly enhance how you construct and work with hypotheses. While all hypotheses serve the essential function of guiding your study, there are varying purposes among the types of hypotheses. In addition, all hypotheses stand in contrast to the null hypothesis, or the assumption that there is no significant relationship between the variables .
Here, we explore various kinds of hypotheses to provide you with the tools needed to craft effective hypotheses for your specific research needs. Bear in mind that many of these hypothesis types may overlap with one another, and the specific type that is typically used will likely depend on the area of research and methodology you are following.
Null hypothesis
The null hypothesis is a statement that there is no effect or relationship between the variables being studied. In statistical terms, it serves as the default assumption that any observed differences are due to random chance.
For example, if you're studying the effect of a drug on blood pressure, the null hypothesis might state that the drug has no effect.
Alternative hypothesis
Contrary to the null hypothesis, the alternative hypothesis suggests that there is a significant relationship or effect between variables.
Using the drug example, the alternative hypothesis would posit that the drug does indeed affect blood pressure. This is what researchers aim to prove.
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Simple hypothesis
A simple hypothesis makes a prediction about the relationship between two variables, and only two variables.
For example, "Increased study time results in better exam scores." Here, "study time" and "exam scores" are the only variables involved.
Complex hypothesis
A complex hypothesis, as the name suggests, involves more than two variables. For instance, "Increased study time and access to resources result in better exam scores." Here, "study time," "access to resources," and "exam scores" are all variables.
This hypothesis refers to multiple potential mediating variables. Other hypotheses could also include predictions about variables that moderate the relationship between the independent variable and dependent variable .
Directional hypothesis
A directional hypothesis specifies the direction of the expected relationship between variables. For example, "Eating more fruits and vegetables leads to a decrease in heart disease."
Here, the direction of heart disease is explicitly predicted to decrease, due to effects from eating more fruits and vegetables. All hypotheses typically specify the expected direction of the relationship between the independent and dependent variable, such that researchers can test if this prediction holds in their data analysis .
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Statistical hypothesis
A statistical hypothesis is one that is testable through statistical methods, providing a numerical value that can be analyzed. This is commonly seen in quantitative research .
For example, "There is a statistically significant difference in test scores between students who study for one hour and those who study for two."
Empirical hypothesis
An empirical hypothesis is derived from observations and is tested through empirical methods, often through experimentation or survey data . Empirical hypotheses may also be assessed with statistical analyses.
For example, "Regular exercise is correlated with a lower incidence of depression," could be tested through surveys that measure exercise frequency and depression levels.
Causal hypothesis
A causal hypothesis proposes that one variable causes a change in another. This type of hypothesis is often tested through controlled experiments.
For example, "Smoking causes lung cancer," assumes a direct causal relationship.
Associative hypothesis
Unlike causal hypotheses, associative hypotheses suggest a relationship between variables but do not imply causation.
For instance, "People who smoke are more likely to get lung cancer," notes an association but doesn't claim that smoking causes lung cancer directly.
Relational hypothesis
A relational hypothesis explores the relationship between two or more variables but doesn't specify the nature of the relationship.
For example, "There is a relationship between diet and heart health," leaves the nature of the relationship (causal, associative, etc.) open to interpretation.
Logical hypothesis
A logical hypothesis is based on sound reasoning and logical principles. It's often used in theoretical research to explore abstract concepts, rather than being based on empirical data.
For example, "If all men are mortal and Socrates is a man, then Socrates is mortal," employs logical reasoning to make its point.
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In any research hypothesis, variables play a critical role. These are the elements or factors that the researcher manipulates, controls, or measures. Understanding variables is essential for crafting a clear, testable hypothesis and for the stages of research that follow, such as data collection and analysis.
In the realm of hypotheses, there are generally two types of variables to consider: independent and dependent. Independent variables are what you, as the researcher, manipulate or change in your study. It's considered the cause in the relationship you're investigating. For instance, in a study examining the impact of sleep duration on academic performance, the independent variable would be the amount of sleep participants get.
Conversely, the dependent variable is the outcome you measure to gauge the effect of your manipulation. It's the effect in the cause-and-effect relationship. The dependent variable thus refers to the main outcome of interest in your study. In the same sleep study example, the academic performance, perhaps measured by exam scores or GPA, would be the dependent variable.
Beyond these two primary types, you might also encounter control variables. These are variables that could potentially influence the outcome and are therefore kept constant to isolate the relationship between the independent and dependent variables . For example, in the sleep and academic performance study, control variables could include age, diet, or even the subject of study.
By clearly identifying and understanding the roles of these variables in your hypothesis, you set the stage for a methodologically sound research project. It helps you develop focused research questions, design appropriate experiments or observations, and carry out meaningful data analysis . It's a step that lays the groundwork for the success of your entire study.
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Crafting a strong, testable hypothesis is crucial for the success of any research project. It sets the stage for everything from your study design to data collection and analysis . Below are some key considerations to keep in mind when formulating your hypothesis:
- Be specific : A vague hypothesis can lead to ambiguous results and interpretations . Clearly define your variables and the expected relationship between them.
- Ensure testability : A good hypothesis should be testable through empirical means, whether by observation , experimentation, or other forms of data analysis.
- Ground in literature : Before creating your hypothesis, consult existing research and theories. This not only helps you identify gaps in current knowledge but also gives you valuable context and credibility for crafting your hypothesis.
- Use simple language : While your hypothesis should be conceptually sound, it doesn't have to be complicated. Aim for clarity and simplicity in your wording.
- State direction, if applicable : If your hypothesis involves a directional outcome (e.g., "increase" or "decrease"), make sure to specify this. You also need to think about how you will measure whether or not the outcome moved in the direction you predicted.
- Keep it focused : One of the common pitfalls in hypothesis formulation is trying to answer too many questions at once. Keep your hypothesis focused on a specific issue or relationship.
- Account for control variables : Identify any variables that could potentially impact the outcome and consider how you will control for them in your study.
- Be ethical : Make sure your hypothesis and the methods for testing it comply with ethical standards , particularly if your research involves human or animal subjects.
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Designing your study involves multiple key phases that help ensure the rigor and validity of your research. Here we discuss these crucial components in more detail.
Literature review
Starting with a comprehensive literature review is essential. This step allows you to understand the existing body of knowledge related to your hypothesis and helps you identify gaps that your research could fill. Your research should aim to contribute some novel understanding to existing literature, and your hypotheses can reflect this. A literature review also provides valuable insights into how similar research projects were executed, thereby helping you fine-tune your own approach.
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Research methods
Choosing the right research methods is critical. Whether it's a survey, an experiment, or observational study, the methodology should be the most appropriate for testing your hypothesis. Your choice of methods will also depend on whether your research is quantitative, qualitative, or mixed-methods. Make sure the chosen methods align well with the variables you are studying and the type of data you need.
Preliminary research
Before diving into a full-scale study, it’s often beneficial to conduct preliminary research or a pilot study . This allows you to test your research methods on a smaller scale, refine your tools, and identify any potential issues. For instance, a pilot survey can help you determine if your questions are clear and if the survey effectively captures the data you need. This step can save you both time and resources in the long run.
Data analysis
Finally, planning your data analysis in advance is crucial for a successful study. Decide which statistical or analytical tools are most suited for your data type and research questions . For quantitative research, you might opt for t-tests, ANOVA, or regression analyses. For qualitative research , thematic analysis or grounded theory may be more appropriate. This phase is integral for interpreting your results and drawing meaningful conclusions in relation to your research question.
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How to Write a Research Hypothesis
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Since grade school, we've all been familiar with hypotheses. The hypothesis is an essential step of the scientific method. But what makes an effective research hypothesis, how do you create one, and what types of hypotheses are there? We answer these questions and more.
Updated on April 27, 2022
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What is a research hypothesis?
General hypothesis.
Since grade school, we've all been familiar with the term “hypothesis.” A hypothesis is a fact-based guess or prediction that has not been proven. It is an essential step of the scientific method. The hypothesis of a study is a drive for experimentation to either prove the hypothesis or dispute it.
Research Hypothesis
A research hypothesis is more specific than a general hypothesis. It is an educated, expected prediction of the outcome of a study that is testable.
What makes an effective research hypothesis?
A good research hypothesis is a clear statement of the relationship between a dependent variable(s) and independent variable(s) relevant to the study that can be disproven.
Research hypothesis checklist
Once you've written a possible hypothesis, make sure it checks the following boxes:
- It must be testable: You need a means to prove your hypothesis. If you can't test it, it's not a hypothesis.
- It must include a dependent and independent variable: At least one independent variable ( cause ) and one dependent variable ( effect ) must be included.
- The language must be easy to understand: Be as clear and concise as possible. Nothing should be left to interpretation.
- It must be relevant to your research topic: You probably shouldn't be talking about cats and dogs if your research topic is outer space. Stay relevant to your topic.
How to create an effective research hypothesis
Pose it as a question first.
Start your research hypothesis from a journalistic approach. Ask one of the five W's: Who, what, when, where, or why.
A possible initial question could be: Why is the sky blue?
Do the preliminary research
Once you have a question in mind, read research around your topic. Collect research from academic journals.
If you're looking for information about the sky and why it is blue, research information about the atmosphere, weather, space, the sun, etc.
Write a draft hypothesis
Once you're comfortable with your subject and have preliminary knowledge, create a working hypothesis. Don't stress much over this. Your first hypothesis is not permanent. Look at it as a draft.
Your first draft of a hypothesis could be: Certain molecules in the Earth's atmosphere are responsive to the sky being the color blue.
Make your working draft perfect
Take your working hypothesis and make it perfect. Narrow it down to include only the information listed in the “Research hypothesis checklist” above.
Now that you've written your working hypothesis, narrow it down. Your new hypothesis could be: Light from the sun hitting oxygen molecules in the sky makes the color of the sky appear blue.
Write a null hypothesis
Your null hypothesis should be the opposite of your research hypothesis. It should be able to be disproven by your research.
In this example, your null hypothesis would be: Light from the sun hitting oxygen molecules in the sky does not make the color of the sky appear blue.
Why is it important to have a clear, testable hypothesis?
One of the main reasons a manuscript can be rejected from a journal is because of a weak hypothesis. “Poor hypothesis, study design, methodology, and improper use of statistics are other reasons for rejection of a manuscript,” says Dr. Ish Kumar Dhammi and Dr. Rehan-Ul-Haq in Indian Journal of Orthopaedics.
According to Dr. James M. Provenzale in American Journal of Roentgenology , “The clear declaration of a research question (or hypothesis) in the Introduction is critical for reviewers to understand the intent of the research study. It is best to clearly state the study goal in plain language (for example, “We set out to determine whether condition x produces condition y.”) An insufficient problem statement is one of the more common reasons for manuscript rejection.”
Characteristics that make a hypothesis weak include:
- Unclear variables
- Unoriginality
- Too general
- Too specific
A weak hypothesis leads to weak research and methods . The goal of a paper is to prove or disprove a hypothesis - or to prove or disprove a null hypothesis. If the hypothesis is not a dependent variable of what is being studied, the paper's methods should come into question.
A strong hypothesis is essential to the scientific method. A hypothesis states an assumed relationship between at least two variables and the experiment then proves or disproves that relationship with statistical significance. Without a proven and reproducible relationship, the paper feeds into the reproducibility crisis. Learn more about writing for reproducibility .
In a study published in The Journal of Obstetrics and Gynecology of India by Dr. Suvarna Satish Khadilkar, she reviewed 400 rejected manuscripts to see why they were rejected. Her studies revealed that poor methodology was a top reason for the submission having a final disposition of rejection.
Aside from publication chances, Dr. Gareth Dyke believes a clear hypothesis helps efficiency.
“Developing a clear and testable hypothesis for your research project means that you will not waste time, energy, and money with your work,” said Dyke. “Refining a hypothesis that is both meaningful, interesting, attainable, and testable is the goal of all effective research.”
Types of research hypotheses
There can be overlap in these types of hypotheses.
Simple hypothesis
A simple hypothesis is a hypothesis at its most basic form. It shows the relationship of one independent and one independent variable.
Example: Drinking soda (independent variable) every day leads to obesity (dependent variable).
Complex hypothesis
A complex hypothesis shows the relationship of two or more independent and dependent variables.
Example: Drinking soda (independent variable) every day leads to obesity (dependent variable) and heart disease (dependent variable).
Directional hypothesis
A directional hypothesis guesses which way the results of an experiment will go. It uses words like increase, decrease, higher, lower, positive, negative, more, or less. It is also frequently used in statistics.
Example: Humans exposed to radiation have a higher risk of cancer than humans not exposed to radiation.
Non-directional hypothesis
A non-directional hypothesis says there will be an effect on the dependent variable, but it does not say which direction.
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Associative hypothesis
An associative hypothesis says that when one variable changes, so does the other variable.
Alternative hypothesis
An alternative hypothesis states that the variables have a relationship.
- The opposite of a null hypothesis
Example: An apple a day keeps the doctor away.
Null hypothesis
A null hypothesis states that there is no relationship between the two variables. It is posed as the opposite of what the alternative hypothesis states.
Researchers use a null hypothesis to work to be able to reject it. A null hypothesis:
- Can never be proven
- Can only be rejected
- Is the opposite of an alternative hypothesis
Example: An apple a day does not keep the doctor away.
Logical hypothesis
A logical hypothesis is a suggested explanation while using limited evidence.
Example: Bats can navigate in the dark better than tigers.
In this hypothesis, the researcher knows that tigers cannot see in the dark, and bats mostly live in darkness.
Empirical hypothesis
An empirical hypothesis is also called a “working hypothesis.” It uses the trial and error method and changes around the independent variables.
- An apple a day keeps the doctor away.
- Two apples a day keep the doctor away.
- Three apples a day keep the doctor away.
In this case, the research changes the hypothesis as the researcher learns more about his/her research.
Statistical hypothesis
A statistical hypothesis is a look of a part of a population or statistical model. This type of hypothesis is especially useful if you are making a statement about a large population. Instead of having to test the entire population of Illinois, you could just use a smaller sample of people who live there.
Example: 70% of people who live in Illinois are iron deficient.
Causal hypothesis
A causal hypothesis states that the independent variable will have an effect on the dependent variable.
Example: Using tobacco products causes cancer.
Final thoughts
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What is and How to Write a Good Hypothesis in Research?
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One of the most important aspects of conducting research is constructing a strong hypothesis. But what makes a hypothesis in research effective? In this article, we’ll look at the difference between a hypothesis and a research question, as well as the elements of a good hypothesis in research. We’ll also include some examples of effective hypotheses, and what pitfalls to avoid.
What is a Hypothesis in Research?
Simply put, a hypothesis is a research question that also includes the predicted or expected result of the research. Without a hypothesis, there can be no basis for a scientific or research experiment. As such, it is critical that you carefully construct your hypothesis by being deliberate and thorough, even before you set pen to paper. Unless your hypothesis is clearly and carefully constructed, any flaw can have an adverse, and even grave, effect on the quality of your experiment and its subsequent results.
Research Question vs Hypothesis
It’s easy to confuse research questions with hypotheses, and vice versa. While they’re both critical to the Scientific Method, they have very specific differences. Primarily, a research question, just like a hypothesis, is focused and concise. But a hypothesis includes a prediction based on the proposed research, and is designed to forecast the relationship of and between two (or more) variables. Research questions are open-ended, and invite debate and discussion, while hypotheses are closed, e.g. “The relationship between A and B will be C.”
A hypothesis is generally used if your research topic is fairly well established, and you are relatively certain about the relationship between the variables that will be presented in your research. Since a hypothesis is ideally suited for experimental studies, it will, by its very existence, affect the design of your experiment. The research question is typically used for new topics that have not yet been researched extensively. Here, the relationship between different variables is less known. There is no prediction made, but there may be variables explored. The research question can be casual in nature, simply trying to understand if a relationship even exists, descriptive or comparative.
How to Write Hypothesis in Research
Writing an effective hypothesis starts before you even begin to type. Like any task, preparation is key, so you start first by conducting research yourself, and reading all you can about the topic that you plan to research. From there, you’ll gain the knowledge you need to understand where your focus within the topic will lie.
Remember that a hypothesis is a prediction of the relationship that exists between two or more variables. Your job is to write a hypothesis, and design the research, to “prove” whether or not your prediction is correct. A common pitfall is to use judgments that are subjective and inappropriate for the construction of a hypothesis. It’s important to keep the focus and language of your hypothesis objective.
An effective hypothesis in research is clearly and concisely written, and any terms or definitions clarified and defined. Specific language must also be used to avoid any generalities or assumptions.
Use the following points as a checklist to evaluate the effectiveness of your research hypothesis:
- Predicts the relationship and outcome
- Simple and concise – avoid wordiness
- Clear with no ambiguity or assumptions about the readers’ knowledge
- Observable and testable results
- Relevant and specific to the research question or problem
Research Hypothesis Example
Perhaps the best way to evaluate whether or not your hypothesis is effective is to compare it to those of your colleagues in the field. There is no need to reinvent the wheel when it comes to writing a powerful research hypothesis. As you’re reading and preparing your hypothesis, you’ll also read other hypotheses. These can help guide you on what works, and what doesn’t, when it comes to writing a strong research hypothesis.
Here are a few generic examples to get you started.
Eating an apple each day, after the age of 60, will result in a reduction of frequency of physician visits.
Budget airlines are more likely to receive more customer complaints. A budget airline is defined as an airline that offers lower fares and fewer amenities than a traditional full-service airline. (Note that the term “budget airline” is included in the hypothesis.
Workplaces that offer flexible working hours report higher levels of employee job satisfaction than workplaces with fixed hours.
Each of the above examples are specific, observable and measurable, and the statement of prediction can be verified or shown to be false by utilizing standard experimental practices. It should be noted, however, that often your hypothesis will change as your research progresses.
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How to Write a Hypothesis – Steps & Tips
Published by Alaxendra Bets at August 14th, 2021 , Revised On October 26, 2023
What is a Research Hypothesis?
You can test a research statement with the help of experimental or theoretical research, known as a hypothesis.
If you want to find out the similarities, differences, and relationships between variables, you must write a testable hypothesis before compiling the data, performing analysis, and generating results to complete.
The data analysis and findings will help you test the hypothesis and see whether it is true or false. Here is all you need to know about how to write a hypothesis for a dissertation .
Research Hypothesis Definition
Not sure what the meaning of the research hypothesis is?
A research hypothesis predicts an answer to the research question based on existing theoretical knowledge or experimental data.
Some studies may have multiple hypothesis statements depending on the research question(s). A research hypothesis must be based on formulas, facts, and theories. It should be testable by data analysis, observations, experiments, or other scientific methodologies that can refute or support the statement.
Variables in Hypothesis
Developing a hypothesis is easy. Most research studies have two or more variables in the hypothesis, particularly studies involving correlational and experimental research. The researcher can control or change the independent variable(s) while measuring and observing the independent variable(s).
“How long a student sleeps affects test scores.”
In the above statement, the dependent variable is the test score, while the independent variable is the length of time spent in sleep. Developing a hypothesis will be easy if you know your research’s dependent and independent variables.
Once you have developed a thesis statement, questions such as how to write a hypothesis for the dissertation and how to test a research hypothesis become pretty straightforward.
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Step-by-Step Guide on How to Write a Hypothesis
Here are the steps involved in how to write a hypothesis for a dissertation.
Step 1: Start with a Research Question
- Begin by asking a specific question about a topic of interest.
- This question should be clear, concise, and researchable.
Example: Does exposure to sunlight affect plant growth?
Step 2: Do Preliminary Research
- Before formulating a hypothesis, conduct background research to understand existing knowledge on the topic.
- Familiarise yourself with prior studies, theories, or observations related to the research question.
Step 3: Define Variables
- Independent Variable (IV): The factor that you change or manipulate in an experiment.
- Dependent Variable (DV): The factor that you measure.
Example: IV: Amount of sunlight exposure (e.g., 2 hours/day, 4 hours/day, 8 hours/day) DV: Plant growth (e.g., height in centimetres)
Step 4: Formulate the Hypothesis
- A hypothesis is a statement that predicts the relationship between variables.
- It is often written as an “if-then” statement.
Example: If plants receive more sunlight, then they will grow taller.
Step 5: Ensure it is Testable
A good hypothesis is empirically testable. This means you should be able to design an experiment or observation to test its validity.
Example: You can set up an experiment where plants are exposed to varying amounts of sunlight and then measure their growth over a period of time.
Step 6: Consider Potential Confounding Variables
- Confounding variables are factors other than the independent variable that might affect the outcome.
- It is important to identify these to ensure that they do not skew your results.
Example: Soil quality, water frequency, or type of plant can all affect growth. Consider keeping these constant in your experiment.
Step 7: Write the Null Hypothesis
- The null hypothesis is a statement that there is no effect or no relationship between the variables.
- It is what you aim to disprove or reject through your research.
Example: There is no difference in plant growth regardless of the amount of sunlight exposure.
Step 8: Test your Hypothesis
Design an experiment or conduct observations to test your hypothesis.
Example: Grow three sets of plants: one set exposed to 2 hours of sunlight daily, another exposed to 4 hours, and a third exposed to 8 hours. Measure and compare their growth after a set period.
Step 9: Analyse the Results
After testing, review your data to determine if it supports your hypothesis.
Step 10: Draw Conclusions
- Based on your findings, determine whether you can accept or reject the hypothesis.
- Remember, even if you reject your hypothesis, it’s a valuable result. It can guide future research and refine questions.
Three Ways to Phrase a Hypothesis
Try to use “if”… and “then”… to identify the variables. The independent variable should be present in the first part of the hypothesis, while the dependent variable will form the second part of the statement. Consider understanding the below research hypothesis example to create a specific, clear, and concise research hypothesis;
If an obese lady starts attending Zomba fitness classes, her health will improve.
In academic research, you can write the predicted variable relationship directly because most research studies correlate terms.
The number of Zomba fitness classes attended by the obese lady has a positive effect on health.
If your research compares two groups, then you can develop a hypothesis statement on their differences.
An obese lady who attended most Zumba fitness classes will have better health than those who attended a few.
How to Write a Null Hypothesis
If a statistical analysis is involved in your research, then you must create a null hypothesis. If you find any relationship between the variables, then the null hypothesis will be the default position that there is no relationship between them. H0 is the symbol for the null hypothesis, while the hypothesis is represented as H1. The null hypothesis will also answer your question, “How to test the research hypothesis in the dissertation.”
H0: The number of Zumba fitness classes attended by the obese lady does not affect her health.
H1: The number of Zumba fitness classes attended by obese lady positively affects health.
Also see: Your Dissertation in Education
Hypothesis Examples
Research Question: Does the amount of sunlight a plant receives affect its growth? Hypothesis: Plants that receive more sunlight will grow taller than plants that receive less sunlight.
Research Question: Do students who eat breakfast perform better in school exams than those who don’t? Hypothesis: Students who eat a morning breakfast will score higher on school exams compared to students who skip breakfast.
Research Question: Does listening to music while studying impact a student’s ability to retain information? Hypothesis 1 (Directional): Students who listen to music while studying will retain less information than those who study in silence. Hypothesis 2 (Non-directional): There will be a difference in information retention between students who listen to music while studying and those who study in silence.
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If you are unsure about how to rest a research hypothesis in a dissertation or simply unsure about how to develop a hypothesis for your research, then you can take advantage of our dissertation services which cover every tiny aspect of a dissertation project you might need help with including but not limited to setting up a hypothesis and research questions, help with individual chapters , full dissertation writing , statistical analysis , and much more.
Frequently Asked Questions
What are the 5 rules for writing a good hypothesis.
- Clear Statement: State a clear relationship between variables.
- Testable: Ensure it can be investigated and measured.
- Specific: Avoid vague terms, be precise in predictions.
- Falsifiable: Design to allow potential disproof.
- Relevant: Address research question and align with existing knowledge.
What is a hypothesis in simple words?
A hypothesis is an educated guess or prediction about something that can be tested. It is a statement that suggests a possible explanation for an event or phenomenon based on prior knowledge or observation. Scientists use hypotheses as a starting point for experiments to discover if they are true or false.
What is the hypothesis and examples?
A hypothesis is a testable prediction or explanation for an observation or phenomenon. For example, if plants are given sunlight, then they will grow. In this case, the hypothesis suggests that sunlight has a positive effect on plant growth. It can be tested by experimenting with plants in varying light conditions.
What is the hypothesis in research definition?
A hypothesis in research is a clear, testable statement predicting the possible outcome of a study based on prior knowledge and observation. It serves as the foundation for conducting experiments or investigations. Researchers test the validity of the hypothesis to draw conclusions and advance knowledge in a particular field.
Why is it called a hypothesis?
The term “hypothesis” originates from the Greek word “hypothesis,” which means “base” or “foundation.” It’s used to describe a foundational statement or proposition that can be tested. In scientific contexts, it denotes a tentative explanation for a phenomenon, serving as a starting point for investigation or experimentation.
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How to Write a Great Hypothesis
Hypothesis Definition, Format, Examples, and Tips
Verywell / Alex Dos Diaz
- The Scientific Method
Hypothesis Format
Falsifiability of a hypothesis.
- Operationalization
Hypothesis Types
Hypotheses examples.
- Collecting Data
A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process.
Consider a study designed to examine the relationship between sleep deprivation and test performance. The hypothesis might be: "This study is designed to assess the hypothesis that sleep-deprived people will perform worse on a test than individuals who are not sleep-deprived."
At a Glance
A hypothesis is crucial to scientific research because it offers a clear direction for what the researchers are looking to find. This allows them to design experiments to test their predictions and add to our scientific knowledge about the world. This article explores how a hypothesis is used in psychology research, how to write a good hypothesis, and the different types of hypotheses you might use.
The Hypothesis in the Scientific Method
In the scientific method , whether it involves research in psychology, biology, or some other area, a hypothesis represents what the researchers think will happen in an experiment. The scientific method involves the following steps:
- Forming a question
- Performing background research
- Creating a hypothesis
- Designing an experiment
- Collecting data
- Analyzing the results
- Drawing conclusions
- Communicating the results
The hypothesis is a prediction, but it involves more than a guess. Most of the time, the hypothesis begins with a question which is then explored through background research. At this point, researchers then begin to develop a testable hypothesis.
Unless you are creating an exploratory study, your hypothesis should always explain what you expect to happen.
In a study exploring the effects of a particular drug, the hypothesis might be that researchers expect the drug to have some type of effect on the symptoms of a specific illness. In psychology, the hypothesis might focus on how a certain aspect of the environment might influence a particular behavior.
Remember, a hypothesis does not have to be correct. While the hypothesis predicts what the researchers expect to see, the goal of the research is to determine whether this guess is right or wrong. When conducting an experiment, researchers might explore numerous factors to determine which ones might contribute to the ultimate outcome.
In many cases, researchers may find that the results of an experiment do not support the original hypothesis. When writing up these results, the researchers might suggest other options that should be explored in future studies.
In many cases, researchers might draw a hypothesis from a specific theory or build on previous research. For example, prior research has shown that stress can impact the immune system. So a researcher might hypothesize: "People with high-stress levels will be more likely to contract a common cold after being exposed to the virus than people who have low-stress levels."
In other instances, researchers might look at commonly held beliefs or folk wisdom. "Birds of a feather flock together" is one example of folk adage that a psychologist might try to investigate. The researcher might pose a specific hypothesis that "People tend to select romantic partners who are similar to them in interests and educational level."
Elements of a Good Hypothesis
So how do you write a good hypothesis? When trying to come up with a hypothesis for your research or experiments, ask yourself the following questions:
- Is your hypothesis based on your research on a topic?
- Can your hypothesis be tested?
- Does your hypothesis include independent and dependent variables?
Before you come up with a specific hypothesis, spend some time doing background research. Once you have completed a literature review, start thinking about potential questions you still have. Pay attention to the discussion section in the journal articles you read . Many authors will suggest questions that still need to be explored.
How to Formulate a Good Hypothesis
To form a hypothesis, you should take these steps:
- Collect as many observations about a topic or problem as you can.
- Evaluate these observations and look for possible causes of the problem.
- Create a list of possible explanations that you might want to explore.
- After you have developed some possible hypotheses, think of ways that you could confirm or disprove each hypothesis through experimentation. This is known as falsifiability.
In the scientific method , falsifiability is an important part of any valid hypothesis. In order to test a claim scientifically, it must be possible that the claim could be proven false.
Students sometimes confuse the idea of falsifiability with the idea that it means that something is false, which is not the case. What falsifiability means is that if something was false, then it is possible to demonstrate that it is false.
One of the hallmarks of pseudoscience is that it makes claims that cannot be refuted or proven false.
The Importance of Operational Definitions
A variable is a factor or element that can be changed and manipulated in ways that are observable and measurable. However, the researcher must also define how the variable will be manipulated and measured in the study.
Operational definitions are specific definitions for all relevant factors in a study. This process helps make vague or ambiguous concepts detailed and measurable.
For example, a researcher might operationally define the variable " test anxiety " as the results of a self-report measure of anxiety experienced during an exam. A "study habits" variable might be defined by the amount of studying that actually occurs as measured by time.
These precise descriptions are important because many things can be measured in various ways. Clearly defining these variables and how they are measured helps ensure that other researchers can replicate your results.
Replicability
One of the basic principles of any type of scientific research is that the results must be replicable.
Replication means repeating an experiment in the same way to produce the same results. By clearly detailing the specifics of how the variables were measured and manipulated, other researchers can better understand the results and repeat the study if needed.
Some variables are more difficult than others to define. For example, how would you operationally define a variable such as aggression ? For obvious ethical reasons, researchers cannot create a situation in which a person behaves aggressively toward others.
To measure this variable, the researcher must devise a measurement that assesses aggressive behavior without harming others. The researcher might utilize a simulated task to measure aggressiveness in this situation.
Hypothesis Checklist
- Does your hypothesis focus on something that you can actually test?
- Does your hypothesis include both an independent and dependent variable?
- Can you manipulate the variables?
- Can your hypothesis be tested without violating ethical standards?
The hypothesis you use will depend on what you are investigating and hoping to find. Some of the main types of hypotheses that you might use include:
- Simple hypothesis : This type of hypothesis suggests there is a relationship between one independent variable and one dependent variable.
- Complex hypothesis : This type suggests a relationship between three or more variables, such as two independent and dependent variables.
- Null hypothesis : This hypothesis suggests no relationship exists between two or more variables.
- Alternative hypothesis : This hypothesis states the opposite of the null hypothesis.
- Statistical hypothesis : This hypothesis uses statistical analysis to evaluate a representative population sample and then generalizes the findings to the larger group.
- Logical hypothesis : This hypothesis assumes a relationship between variables without collecting data or evidence.
A hypothesis often follows a basic format of "If {this happens} then {this will happen}." One way to structure your hypothesis is to describe what will happen to the dependent variable if you change the independent variable .
The basic format might be: "If {these changes are made to a certain independent variable}, then we will observe {a change in a specific dependent variable}."
A few examples of simple hypotheses:
- "Students who eat breakfast will perform better on a math exam than students who do not eat breakfast."
- "Students who experience test anxiety before an English exam will get lower scores than students who do not experience test anxiety."
- "Motorists who talk on the phone while driving will be more likely to make errors on a driving course than those who do not talk on the phone."
- "Children who receive a new reading intervention will have higher reading scores than students who do not receive the intervention."
Examples of a complex hypothesis include:
- "People with high-sugar diets and sedentary activity levels are more likely to develop depression."
- "Younger people who are regularly exposed to green, outdoor areas have better subjective well-being than older adults who have limited exposure to green spaces."
Examples of a null hypothesis include:
- "There is no difference in anxiety levels between people who take St. John's wort supplements and those who do not."
- "There is no difference in scores on a memory recall task between children and adults."
- "There is no difference in aggression levels between children who play first-person shooter games and those who do not."
Examples of an alternative hypothesis:
- "People who take St. John's wort supplements will have less anxiety than those who do not."
- "Adults will perform better on a memory task than children."
- "Children who play first-person shooter games will show higher levels of aggression than children who do not."
Collecting Data on Your Hypothesis
Once a researcher has formed a testable hypothesis, the next step is to select a research design and start collecting data. The research method depends largely on exactly what they are studying. There are two basic types of research methods: descriptive research and experimental research.
Descriptive Research Methods
Descriptive research such as case studies , naturalistic observations , and surveys are often used when conducting an experiment is difficult or impossible. These methods are best used to describe different aspects of a behavior or psychological phenomenon.
Once a researcher has collected data using descriptive methods, a correlational study can examine how the variables are related. This research method might be used to investigate a hypothesis that is difficult to test experimentally.
Experimental Research Methods
Experimental methods are used to demonstrate causal relationships between variables. In an experiment, the researcher systematically manipulates a variable of interest (known as the independent variable) and measures the effect on another variable (known as the dependent variable).
Unlike correlational studies, which can only be used to determine if there is a relationship between two variables, experimental methods can be used to determine the actual nature of the relationship—whether changes in one variable actually cause another to change.
The hypothesis is a critical part of any scientific exploration. It represents what researchers expect to find in a study or experiment. In situations where the hypothesis is unsupported by the research, the research still has value. Such research helps us better understand how different aspects of the natural world relate to one another. It also helps us develop new hypotheses that can then be tested in the future.
Thompson WH, Skau S. On the scope of scientific hypotheses . R Soc Open Sci . 2023;10(8):230607. doi:10.1098/rsos.230607
Taran S, Adhikari NKJ, Fan E. Falsifiability in medicine: what clinicians can learn from Karl Popper [published correction appears in Intensive Care Med. 2021 Jun 17;:]. Intensive Care Med . 2021;47(9):1054-1056. doi:10.1007/s00134-021-06432-z
Eyler AA. Research Methods for Public Health . 1st ed. Springer Publishing Company; 2020. doi:10.1891/9780826182067.0004
Nosek BA, Errington TM. What is replication ? PLoS Biol . 2020;18(3):e3000691. doi:10.1371/journal.pbio.3000691
Aggarwal R, Ranganathan P. Study designs: Part 2 - Descriptive studies . Perspect Clin Res . 2019;10(1):34-36. doi:10.4103/picr.PICR_154_18
Nevid J. Psychology: Concepts and Applications. Wadworth, 2013.
By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."
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What Is A Research (Scientific) Hypothesis? A plain-language explainer + examples
By: Derek Jansen (MBA) | Reviewed By: Dr Eunice Rautenbach | June 2020
If you’re new to the world of research, or it’s your first time writing a dissertation or thesis, you’re probably noticing that the words “research hypothesis” and “scientific hypothesis” are used quite a bit, and you’re wondering what they mean in a research context .
“Hypothesis” is one of those words that people use loosely, thinking they understand what it means. However, it has a very specific meaning within academic research. So, it’s important to understand the exact meaning before you start hypothesizing.
Research Hypothesis 101
- What is a hypothesis ?
- What is a research hypothesis (scientific hypothesis)?
- Requirements for a research hypothesis
- Definition of a research hypothesis
- The null hypothesis
What is a hypothesis?
Let’s start with the general definition of a hypothesis (not a research hypothesis or scientific hypothesis), according to the Cambridge Dictionary:
Hypothesis: an idea or explanation for something that is based on known facts but has not yet been proved.
In other words, it’s a statement that provides an explanation for why or how something works, based on facts (or some reasonable assumptions), but that has not yet been specifically tested . For example, a hypothesis might look something like this:
Hypothesis: sleep impacts academic performance.
This statement predicts that academic performance will be influenced by the amount and/or quality of sleep a student engages in – sounds reasonable, right? It’s based on reasonable assumptions , underpinned by what we currently know about sleep and health (from the existing literature). So, loosely speaking, we could call it a hypothesis, at least by the dictionary definition.
But that’s not good enough…
Unfortunately, that’s not quite sophisticated enough to describe a research hypothesis (also sometimes called a scientific hypothesis), and it wouldn’t be acceptable in a dissertation, thesis or research paper . In the world of academic research, a statement needs a few more criteria to constitute a true research hypothesis .
What is a research hypothesis?
A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes – specificity , clarity and testability .
Let’s take a look at these more closely.
Need a helping hand?
Hypothesis Essential #1: Specificity & Clarity
A good research hypothesis needs to be extremely clear and articulate about both what’ s being assessed (who or what variables are involved ) and the expected outcome (for example, a difference between groups, a relationship between variables, etc.).
Let’s stick with our sleepy students example and look at how this statement could be more specific and clear.
Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.
As you can see, the statement is very specific as it identifies the variables involved (sleep hours and test grades), the parties involved (two groups of students), as well as the predicted relationship type (a positive relationship). There’s no ambiguity or uncertainty about who or what is involved in the statement, and the expected outcome is clear.
Contrast that to the original hypothesis we looked at – “Sleep impacts academic performance” – and you can see the difference. “Sleep” and “academic performance” are both comparatively vague , and there’s no indication of what the expected relationship direction is (more sleep or less sleep). As you can see, specificity and clarity are key.
![research-hypothesis-1 A good research hypothesis needs to be very clear about what’s being assessed and very specific about the expected outcome.](https://gradcoach.com/wp-content/uploads/research-hypothesis-1.png)
Hypothesis Essential #2: Testability (Provability)
A statement must be testable to qualify as a research hypothesis. In other words, there needs to be a way to prove (or disprove) the statement. If it’s not testable, it’s not a hypothesis – simple as that.
For example, consider the hypothesis we mentioned earlier:
Hypothesis: Students who sleep at least 8 hours per night will, on average, achieve higher grades in standardised tests than students who sleep less than 8 hours a night.
We could test this statement by undertaking a quantitative study involving two groups of students, one that gets 8 or more hours of sleep per night for a fixed period, and one that gets less. We could then compare the standardised test results for both groups to see if there’s a statistically significant difference.
Again, if you compare this to the original hypothesis we looked at – “Sleep impacts academic performance” – you can see that it would be quite difficult to test that statement, primarily because it isn’t specific enough. How much sleep? By who? What type of academic performance?
So, remember the mantra – if you can’t test it, it’s not a hypothesis 🙂
![hypothesis-requirement-2 A good research hypothesis must be testable. In other words, you must able to collect observable data in a scientifically rigorous fashion to test it.](https://gradcoach.com/wp-content/uploads/hypothesis-requirement-2.png)
Defining A Research Hypothesis
You’re still with us? Great! Let’s recap and pin down a clear definition of a hypothesis.
A research hypothesis (or scientific hypothesis) is a statement about an expected relationship between variables, or explanation of an occurrence, that is clear, specific and testable.
So, when you write up hypotheses for your dissertation or thesis, make sure that they meet all these criteria. If you do, you’ll not only have rock-solid hypotheses but you’ll also ensure a clear focus for your entire research project.
What about the null hypothesis?
You may have also heard the terms null hypothesis , alternative hypothesis, or H-zero thrown around. At a simple level, the null hypothesis is the counter-proposal to the original hypothesis.
For example, if the hypothesis predicts that there is a relationship between two variables (for example, sleep and academic performance), the null hypothesis would predict that there is no relationship between those variables.
At a more technical level, the null hypothesis proposes that no statistical significance exists in a set of given observations and that any differences are due to chance alone.
And there you have it – hypotheses in a nutshell.
If you have any questions, be sure to leave a comment below and we’ll do our best to help you. If you need hands-on help developing and testing your hypotheses, consider our private coaching service , where we hold your hand through the research journey.
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16 Comments
Very useful information. I benefit more from getting more information in this regard.
Very great insight,educative and informative. Please give meet deep critics on many research data of public international Law like human rights, environment, natural resources, law of the sea etc
In a book I read a distinction is made between null, research, and alternative hypothesis. As far as I understand, alternative and research hypotheses are the same. Can you please elaborate? Best Afshin
This is a self explanatory, easy going site. I will recommend this to my friends and colleagues.
Very good definition. How can I cite your definition in my thesis? Thank you. Is nul hypothesis compulsory in a research?
It’s a counter-proposal to be proven as a rejection
Please what is the difference between alternate hypothesis and research hypothesis?
It is a very good explanation. However, it limits hypotheses to statistically tasteable ideas. What about for qualitative researches or other researches that involve quantitative data that don’t need statistical tests?
In qualitative research, one typically uses propositions, not hypotheses.
could you please elaborate it more
I’ve benefited greatly from these notes, thank you.
This is very helpful
well articulated ideas are presented here, thank you for being reliable sources of information
Excellent. Thanks for being clear and sound about the research methodology and hypothesis (quantitative research)
I have only a simple question regarding the null hypothesis. – Is the null hypothesis (Ho) known as the reversible hypothesis of the alternative hypothesis (H1? – How to test it in academic research?
this is very important note help me much more
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How to write a research hypothesis
Last updated
19 January 2023
Reviewed by
Miroslav Damyanov
Start with a broad subject matter that excites you, so your curiosity will motivate your work. Conduct a literature search to determine the range of questions already addressed and spot any holes in the existing research.
Narrow the topics that interest you and determine your research question. Rather than focusing on a hole in the research, you might choose to challenge an existing assumption, a process called problematization. You may also find yourself with a short list of questions or related topics.
Use the FINER method to determine the single problem you'll address with your research. FINER stands for:
I nteresting
You need a feasible research question, meaning that there is a way to address the question. You should find it interesting, but so should a larger audience. Rather than repeating research that others have already conducted, your research hypothesis should test something novel or unique.
The research must fall into accepted ethical parameters as defined by the government of your country and your university or college if you're an academic. You'll also need to come up with a relevant question since your research should provide a contribution to the existing research area.
This process typically narrows your shortlist down to a single problem you'd like to study and the variable you want to test. You're ready to write your hypothesis statements.
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- Types of research hypotheses
It is important to narrow your topic down to one idea before trying to write your research hypothesis. You'll only test one problem at a time. To do this, you'll write two hypotheses – a null hypothesis (H0) and an alternative hypothesis (Ha).
You'll come across many terms related to developing a research hypothesis or referring to a specific type of hypothesis. Let's take a quick look at these terms.
Null hypothesis
The term null hypothesis refers to a research hypothesis type that assumes no statistically significant relationship exists within a set of observations or data. It represents a claim that assumes that any observed relationship is due to chance. Represented as H0, the null represents the conjecture of the research.
Alternative hypothesis
The alternative hypothesis accompanies the null hypothesis. It states that the situation presented in the null hypothesis is false or untrue, and claims an observed effect in your test. This is typically denoted by Ha or H(n), where “n” stands for the number of alternative hypotheses. You can have more than one alternative hypothesis.
Simple hypothesis
The term simple hypothesis refers to a hypothesis or theory that predicts the relationship between two variables - the independent (predictor) and the dependent (predicted).
Complex hypothesis
The term complex hypothesis refers to a model – either quantitative (mathematical) or qualitative . A complex hypothesis states the surmised relationship between two or more potentially related variables.
Directional hypothesis
When creating a statistical hypothesis, the directional hypothesis (the null hypothesis) states an assumption regarding one parameter of a population. Some academics call this the “one-sided” hypothesis. The alternative hypothesis indicates whether the researcher tests for a positive or negative effect by including either the greater than (">") or less than ("<") sign.
Non-directional hypothesis
We refer to the alternative hypothesis in a statistical research question as a non-directional hypothesis. It includes the not equal ("≠") sign to show that the research tests whether or not an effect exists without specifying the effect's direction (positive or negative).
Associative hypothesis
The term associative hypothesis assumes a link between two variables but stops short of stating that one variable impacts the other. Academic statistical literature asserts in this sense that correlation does not imply causation. So, although the hypothesis notes the correlation between two variables – the independent and dependent - it does not predict how the two interact.
Logical hypothesis
Typically used in philosophy rather than science, researchers can't test a logical hypothesis because the technology or data set doesn't yet exist. A logical hypothesis uses logic as the basis of its assumptions.
In some cases, a logical hypothesis can become an empirical hypothesis once technology provides an opportunity for testing. Until that time, the question remains too expensive or complex to address. Note that a logical hypothesis is not a statistical hypothesis.
Empirical hypothesis
When we consider the opposite of a logical hypothesis, we call this an empirical or working hypothesis. This type of hypothesis considers a scientifically measurable question. A researcher can consider and test an empirical hypothesis through replicable tests, observations, and measurements.
Statistical hypothesis
The term statistical hypothesis refers to a test of a theory that uses representative statistical models to test relationships between variables to draw conclusions regarding a large population. This requires an existing large data set, commonly referred to as big data, or implementing a survey to obtain original statistical information to form a data set for the study.
Testing this type of hypothesis requires the use of random samples. Note that the null and alternative hypotheses are used in statistical hypothesis testing.
Causal hypothesis
The term causal hypothesis refers to a research hypothesis that tests a cause-and-effect relationship. A causal hypothesis is utilized when conducting experimental or quasi-experimental research.
Descriptive hypothesis
The term descriptive hypothesis refers to a research hypothesis used in non-experimental research, specifying an influence in the relationship between two variables.
- What makes an effective research hypothesis?
An effective research hypothesis offers a clearly defined, specific statement, using simple wording that contains no assumptions or generalizations, and that you can test. A well-written hypothesis should predict the tested relationship and its outcome. It contains zero ambiguity and offers results you can observe and test.
The research hypothesis should address a question relevant to a research area. Overall, your research hypothesis needs the following essentials:
Hypothesis Essential #1: Specificity & Clarity
Hypothesis Essential #2: Testability (Provability)
- How to develop a good research hypothesis
In developing your hypothesis statements, you must pre-plan some of your statistical analysis. Once you decide on your problem to examine, determine three aspects:
the parameter you'll test
the test's direction (left-tailed, right-tailed, or non-directional)
the hypothesized parameter value
Any quantitative research includes a hypothesized parameter value of a mean, a proportion, or the difference between two proportions. Here's how to note each parameter:
Single mean (μ)
Paired means (μd)
Single proportion (p)
Difference between two independent means (μ1−μ2)
Difference between two proportions (p1−p2)
Simple linear regression slope (β)
Correlation (ρ)
Defining these parameters and determining whether you want to test the mean, proportion, or differences helps you determine the statistical tests you'll conduct to analyze your data. When writing your hypothesis, you only need to decide which parameter to test and in what overarching way.
The null research hypothesis must include everyday language, in a single sentence, stating the problem you want to solve. Write it as an if-then statement with defined variables. Write an alternative research hypothesis that states the opposite.
- What is the correct format for writing a hypothesis?
The following example shows the proper format and textual content of a hypothesis. It follows commonly accepted academic standards.
Null hypothesis (H0): High school students who participate in varsity sports as opposed to those who do not, fail to score higher on leadership tests than students who do not participate.
Alternative hypothesis (H1): High school students who play a varsity sport as opposed to those who do not participate in team athletics will score higher on leadership tests than students who do not participate in athletics.
The research question tests the correlation between varsity sports participation and leadership qualities expressed as a score on leadership tests. It compares the population of athletes to non-athletes.
- What are the five steps of a hypothesis?
Once you decide on the specific problem or question you want to address, you can write your research hypothesis. Use this five-step system to hone your null hypothesis and generate your alternative hypothesis.
Step 1 : Create your research question. This topic should interest and excite you; answering it provides relevant information to an industry or academic area.
Step 2 : Conduct a literature review to gather essential existing research.
Step 3 : Write a clear, strong, simply worded sentence that explains your test parameter, test direction, and hypothesized parameter.
Step 4 : Read it a few times. Have others read it and ask them what they think it means. Refine your statement accordingly until it becomes understandable to everyone. While not everyone can or will comprehend every research study conducted, any person from the general population should be able to read your hypothesis and alternative hypothesis and understand the essential question you want to answer.
Step 5 : Re-write your null hypothesis until it reads simply and understandably. Write your alternative hypothesis.
What is the Red Queen hypothesis?
Some hypotheses are well-known, such as the Red Queen hypothesis. Choose your wording carefully, since you could become like the famed scientist Dr. Leigh Van Valen. In 1973, Dr. Van Valen proposed the Red Queen hypothesis to describe coevolutionary activity, specifically reciprocal evolutionary effects between species to explain extinction rates in the fossil record.
Essentially, Van Valen theorized that to survive, each species remains in a constant state of adaptation, evolution, and proliferation, and constantly competes for survival alongside other species doing the same. Only by doing this can a species avoid extinction. Van Valen took the hypothesis title from the Lewis Carroll book, "Through the Looking Glass," which contains a key character named the Red Queen who explains to Alice that for all of her running, she's merely running in place.
- Getting started with your research
In conclusion, once you write your null hypothesis (H0) and an alternative hypothesis (Ha), you’ve essentially authored the elevator pitch of your research. These two one-sentence statements describe your topic in simple, understandable terms that both professionals and laymen can understand. They provide the starting point of your research project.
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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles
Edward barroga.
1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.
Glafera Janet Matanguihan
2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.
The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.
INTRODUCTION
Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6
It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4
There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.
DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES
A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5
On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4
Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8
Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12
CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES
Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13
There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10
TYPES OF RESEARCH QUESTIONS AND HYPOTHESES
Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .
Quantitative research questions | Quantitative research hypotheses |
---|---|
Descriptive research questions | Simple hypothesis |
Comparative research questions | Complex hypothesis |
Relationship research questions | Directional hypothesis |
Non-directional hypothesis | |
Associative hypothesis | |
Causal hypothesis | |
Null hypothesis | |
Alternative hypothesis | |
Working hypothesis | |
Statistical hypothesis | |
Logical hypothesis | |
Hypothesis-testing | |
Qualitative research questions | Qualitative research hypotheses |
Contextual research questions | Hypothesis-generating |
Descriptive research questions | |
Evaluation research questions | |
Explanatory research questions | |
Exploratory research questions | |
Generative research questions | |
Ideological research questions | |
Ethnographic research questions | |
Phenomenological research questions | |
Grounded theory questions | |
Qualitative case study questions |
Research questions in quantitative research
In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .
Quantitative research questions | |
---|---|
Descriptive research question | |
- Measures responses of subjects to variables | |
- Presents variables to measure, analyze, or assess | |
What is the proportion of resident doctors in the hospital who have mastered ultrasonography (response of subjects to a variable) as a diagnostic technique in their clinical training? | |
Comparative research question | |
- Clarifies difference between one group with outcome variable and another group without outcome variable | |
Is there a difference in the reduction of lung metastasis in osteosarcoma patients who received the vitamin D adjunctive therapy (group with outcome variable) compared with osteosarcoma patients who did not receive the vitamin D adjunctive therapy (group without outcome variable)? | |
- Compares the effects of variables | |
How does the vitamin D analogue 22-Oxacalcitriol (variable 1) mimic the antiproliferative activity of 1,25-Dihydroxyvitamin D (variable 2) in osteosarcoma cells? | |
Relationship research question | |
- Defines trends, association, relationships, or interactions between dependent variable and independent variable | |
Is there a relationship between the number of medical student suicide (dependent variable) and the level of medical student stress (independent variable) in Japan during the first wave of the COVID-19 pandemic? |
Hypotheses in quantitative research
In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .
Quantitative research hypotheses | |
---|---|
Simple hypothesis | |
- Predicts relationship between single dependent variable and single independent variable | |
If the dose of the new medication (single independent variable) is high, blood pressure (single dependent variable) is lowered. | |
Complex hypothesis | |
- Foretells relationship between two or more independent and dependent variables | |
The higher the use of anticancer drugs, radiation therapy, and adjunctive agents (3 independent variables), the higher would be the survival rate (1 dependent variable). | |
Directional hypothesis | |
- Identifies study direction based on theory towards particular outcome to clarify relationship between variables | |
Privately funded research projects will have a larger international scope (study direction) than publicly funded research projects. | |
Non-directional hypothesis | |
- Nature of relationship between two variables or exact study direction is not identified | |
- Does not involve a theory | |
Women and men are different in terms of helpfulness. (Exact study direction is not identified) | |
Associative hypothesis | |
- Describes variable interdependency | |
- Change in one variable causes change in another variable | |
A larger number of people vaccinated against COVID-19 in the region (change in independent variable) will reduce the region’s incidence of COVID-19 infection (change in dependent variable). | |
Causal hypothesis | |
- An effect on dependent variable is predicted from manipulation of independent variable | |
A change into a high-fiber diet (independent variable) will reduce the blood sugar level (dependent variable) of the patient. | |
Null hypothesis | |
- A negative statement indicating no relationship or difference between 2 variables | |
There is no significant difference in the severity of pulmonary metastases between the new drug (variable 1) and the current drug (variable 2). | |
Alternative hypothesis | |
- Following a null hypothesis, an alternative hypothesis predicts a relationship between 2 study variables | |
The new drug (variable 1) is better on average in reducing the level of pain from pulmonary metastasis than the current drug (variable 2). | |
Working hypothesis | |
- A hypothesis that is initially accepted for further research to produce a feasible theory | |
Dairy cows fed with concentrates of different formulations will produce different amounts of milk. | |
Statistical hypothesis | |
- Assumption about the value of population parameter or relationship among several population characteristics | |
- Validity tested by a statistical experiment or analysis | |
The mean recovery rate from COVID-19 infection (value of population parameter) is not significantly different between population 1 and population 2. | |
There is a positive correlation between the level of stress at the workplace and the number of suicides (population characteristics) among working people in Japan. | |
Logical hypothesis | |
- Offers or proposes an explanation with limited or no extensive evidence | |
If healthcare workers provide more educational programs about contraception methods, the number of adolescent pregnancies will be less. | |
Hypothesis-testing (Quantitative hypothesis-testing research) | |
- Quantitative research uses deductive reasoning. | |
- This involves the formation of a hypothesis, collection of data in the investigation of the problem, analysis and use of the data from the investigation, and drawing of conclusions to validate or nullify the hypotheses. |
Research questions in qualitative research
Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15
There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .
Qualitative research questions | |
---|---|
Contextual research question | |
- Ask the nature of what already exists | |
- Individuals or groups function to further clarify and understand the natural context of real-world problems | |
What are the experiences of nurses working night shifts in healthcare during the COVID-19 pandemic? (natural context of real-world problems) | |
Descriptive research question | |
- Aims to describe a phenomenon | |
What are the different forms of disrespect and abuse (phenomenon) experienced by Tanzanian women when giving birth in healthcare facilities? | |
Evaluation research question | |
- Examines the effectiveness of existing practice or accepted frameworks | |
How effective are decision aids (effectiveness of existing practice) in helping decide whether to give birth at home or in a healthcare facility? | |
Explanatory research question | |
- Clarifies a previously studied phenomenon and explains why it occurs | |
Why is there an increase in teenage pregnancy (phenomenon) in Tanzania? | |
Exploratory research question | |
- Explores areas that have not been fully investigated to have a deeper understanding of the research problem | |
What factors affect the mental health of medical students (areas that have not yet been fully investigated) during the COVID-19 pandemic? | |
Generative research question | |
- Develops an in-depth understanding of people’s behavior by asking ‘how would’ or ‘what if’ to identify problems and find solutions | |
How would the extensive research experience of the behavior of new staff impact the success of the novel drug initiative? | |
Ideological research question | |
- Aims to advance specific ideas or ideologies of a position | |
Are Japanese nurses who volunteer in remote African hospitals able to promote humanized care of patients (specific ideas or ideologies) in the areas of safe patient environment, respect of patient privacy, and provision of accurate information related to health and care? | |
Ethnographic research question | |
- Clarifies peoples’ nature, activities, their interactions, and the outcomes of their actions in specific settings | |
What are the demographic characteristics, rehabilitative treatments, community interactions, and disease outcomes (nature, activities, their interactions, and the outcomes) of people in China who are suffering from pneumoconiosis? | |
Phenomenological research question | |
- Knows more about the phenomena that have impacted an individual | |
What are the lived experiences of parents who have been living with and caring for children with a diagnosis of autism? (phenomena that have impacted an individual) | |
Grounded theory question | |
- Focuses on social processes asking about what happens and how people interact, or uncovering social relationships and behaviors of groups | |
What are the problems that pregnant adolescents face in terms of social and cultural norms (social processes), and how can these be addressed? | |
Qualitative case study question | |
- Assesses a phenomenon using different sources of data to answer “why” and “how” questions | |
- Considers how the phenomenon is influenced by its contextual situation. | |
How does quitting work and assuming the role of a full-time mother (phenomenon assessed) change the lives of women in Japan? |
Qualitative research hypotheses | |
---|---|
Hypothesis-generating (Qualitative hypothesis-generating research) | |
- Qualitative research uses inductive reasoning. | |
- This involves data collection from study participants or the literature regarding a phenomenon of interest, using the collected data to develop a formal hypothesis, and using the formal hypothesis as a framework for testing the hypothesis. | |
- Qualitative exploratory studies explore areas deeper, clarifying subjective experience and allowing formulation of a formal hypothesis potentially testable in a future quantitative approach. |
Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15
Hypotheses in qualitative research
Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1
FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES
Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14
The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14
As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.
Variables | Unclear and weak statement (Statement 1) | Clear and good statement (Statement 2) | Points to avoid |
---|---|---|---|
Research question | Which is more effective between smoke moxibustion and smokeless moxibustion? | “Moreover, regarding smoke moxibustion versus smokeless moxibustion, it remains unclear which is more effective, safe, and acceptable to pregnant women, and whether there is any difference in the amount of heat generated.” | 1) Vague and unfocused questions |
2) Closed questions simply answerable by yes or no | |||
3) Questions requiring a simple choice | |||
Hypothesis | The smoke moxibustion group will have higher cephalic presentation. | “Hypothesis 1. The smoke moxibustion stick group (SM group) and smokeless moxibustion stick group (-SLM group) will have higher rates of cephalic presentation after treatment than the control group. | 1) Unverifiable hypotheses |
Hypothesis 2. The SM group and SLM group will have higher rates of cephalic presentation at birth than the control group. | 2) Incompletely stated groups of comparison | ||
Hypothesis 3. There will be no significant differences in the well-being of the mother and child among the three groups in terms of the following outcomes: premature birth, premature rupture of membranes (PROM) at < 37 weeks, Apgar score < 7 at 5 min, umbilical cord blood pH < 7.1, admission to neonatal intensive care unit (NICU), and intrauterine fetal death.” | 3) Insufficiently described variables or outcomes | ||
Research objective | To determine which is more effective between smoke moxibustion and smokeless moxibustion. | “The specific aims of this pilot study were (a) to compare the effects of smoke moxibustion and smokeless moxibustion treatments with the control group as a possible supplement to ECV for converting breech presentation to cephalic presentation and increasing adherence to the newly obtained cephalic position, and (b) to assess the effects of these treatments on the well-being of the mother and child.” | 1) Poor understanding of the research question and hypotheses |
2) Insufficient description of population, variables, or study outcomes |
a These statements were composed for comparison and illustrative purposes only.
b These statements are direct quotes from Higashihara and Horiuchi. 16
Variables | Unclear and weak statement (Statement 1) | Clear and good statement (Statement 2) | Points to avoid |
---|---|---|---|
Research question | Does disrespect and abuse (D&A) occur in childbirth in Tanzania? | How does disrespect and abuse (D&A) occur and what are the types of physical and psychological abuses observed in midwives’ actual care during facility-based childbirth in urban Tanzania? | 1) Ambiguous or oversimplistic questions |
2) Questions unverifiable by data collection and analysis | |||
Hypothesis | Disrespect and abuse (D&A) occur in childbirth in Tanzania. | Hypothesis 1: Several types of physical and psychological abuse by midwives in actual care occur during facility-based childbirth in urban Tanzania. | 1) Statements simply expressing facts |
Hypothesis 2: Weak nursing and midwifery management contribute to the D&A of women during facility-based childbirth in urban Tanzania. | 2) Insufficiently described concepts or variables | ||
Research objective | To describe disrespect and abuse (D&A) in childbirth in Tanzania. | “This study aimed to describe from actual observations the respectful and disrespectful care received by women from midwives during their labor period in two hospitals in urban Tanzania.” | 1) Statements unrelated to the research question and hypotheses |
2) Unattainable or unexplorable objectives |
a This statement is a direct quote from Shimoda et al. 17
The other statements were composed for comparison and illustrative purposes only.
CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES
To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .
![Click on image to zoom An external file that holds a picture, illustration, etc.
Object name is jkms-37-e121-g001.jpg](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039193/bin/jkms-37-e121-g001.jpg)
Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.
Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12
In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.
![Click on image to zoom An external file that holds a picture, illustration, etc.
Object name is jkms-37-e121-g002.jpg](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039193/bin/jkms-37-e121-g002.jpg)
EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES
- EXAMPLE 1. Descriptive research question (quantitative research)
- - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
- “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
- RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
- EXAMPLE 2. Relationship research question (quantitative research)
- - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
- “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
- Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
- EXAMPLE 3. Comparative research question (quantitative research)
- - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
- “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
- RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
- STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
- EXAMPLE 4. Exploratory research question (qualitative research)
- - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
- “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
- EXAMPLE 5. Relationship research question (quantitative research)
- - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
- “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23
EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES
- EXAMPLE 1. Working hypothesis (quantitative research)
- - A hypothesis that is initially accepted for further research to produce a feasible theory
- “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
- “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
- EXAMPLE 2. Exploratory hypothesis (qualitative research)
- - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
- “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
- “Conclusion
- Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
- EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
- “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
- Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
- EXAMPLE 4. Statistical hypothesis (quantitative research)
- - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
- “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
- “Statistical Analysis
- ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27
EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS
- EXAMPLE 1. Background, hypotheses, and aims are provided
- “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
- “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
- “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
- EXAMPLE 2. Background, hypotheses, and aims are provided
- “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
- “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
- EXAMPLE 3. Background, aim, and hypothesis are provided
- “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
- “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
- “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30
Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.
Disclosure: The authors have no potential conflicts of interest to disclose.
Author Contributions:
- Conceptualization: Barroga E, Matanguihan GJ.
- Methodology: Barroga E, Matanguihan GJ.
- Writing - original draft: Barroga E, Matanguihan GJ.
- Writing - review & editing: Barroga E, Matanguihan GJ.
Learn How To Write A Hypothesis For Your Next Research Project!
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Undoubtedly, research plays a crucial role in substantiating or refuting our assumptions. These assumptions act as potential answers to our questions. Such assumptions, also known as hypotheses, are considered key aspects of research. In this blog, we delve into the significance of hypotheses. And provide insights on how to write them effectively. So, let’s dive in and explore the art of writing hypotheses together.
Table of Contents
What is a Hypothesis?
A hypothesis is a crucial starting point in scientific research. It is an educated guess about the relationship between two or more variables. In other words, a hypothesis acts as a foundation for a researcher to build their study.
Here are some examples of well-crafted hypotheses:
- Increased exposure to natural sunlight improves sleep quality in adults.
A positive relationship between natural sunlight exposure and sleep quality in adult individuals.
- Playing puzzle games on a regular basis enhances problem-solving abilities in children.
Engaging in frequent puzzle gameplay leads to improved problem-solving skills in children.
- Students and improved learning hecks.
S tudents using online paper writing service platforms (as a learning tool for receiving personalized feedback and guidance) will demonstrate improved writing skills. (compared to those who do not utilize such platforms).
- The use of APA format in research papers.
Using the APA format helps students stay organized when writing research papers. Organized students can focus better on their topics and, as a result, produce better quality work.
The Building Blocks of a Hypothesis
To better understand the concept of a hypothesis, let’s break it down into its basic components:
- Variables . A hypothesis involves at least two variables. An independent variable and a dependent variable. The independent variable is the one being changed or manipulated, while the dependent variable is the one being measured or observed.
- Relationship : A hypothesis proposes a relationship or connection between the variables. This could be a cause-and-effect relationship or a correlation between them.
- Testability : A hypothesis should be testable and falsifiable, meaning it can be proven right or wrong through experimentation or observation.
Types of Hypotheses
When learning how to write a hypothesis, it’s essential to understand its main types. These include; alternative hypotheses and null hypotheses. In the following section, we explore both types of hypotheses with examples.
Alternative Hypothesis (H1)
This kind of hypothesis suggests a relationship or effect between the variables. It is the main focus of the study. The researcher wants to either prove or disprove it. Many research divides this hypothesis into two subsections:
- Directional
This type of H1 predicts a specific outcome. Many researchers use this hypothesis to explore the relationship between variables rather than the groups.
- Non-directional
You can take a guess from the name. This type of H1 does not provide a specific prediction for the research outcome.
Here are some examples for your better understanding of how to write a hypothesis.
- Consuming caffeine improves cognitive performance. (This hypothesis predicts that there is a positive relationship between caffeine consumption and cognitive performance.)
- Aerobic exercise leads to reduced blood pressure. (This hypothesis suggests that engaging in aerobic exercise results in lower blood pressure readings.)
- Exposure to nature reduces stress levels among employees. (Here, the hypothesis proposes that employees exposed to natural environments will experience decreased stress levels.)
- Listening to classical music while studying increases memory retention. (This hypothesis speculates that studying with classical music playing in the background boosts students’ ability to retain information.)
- Early literacy intervention improves reading skills in children. (This hypothesis claims that providing early literacy assistance to children results in enhanced reading abilities.)
- Time management in nursing students. ( Students who use a nursing research paper writing service have more time to focus on their studies and can achieve better grades in other subjects. )
Null Hypothesis (H0)
A null hypothesis assumes no relationship or effect between the variables. If the alternative hypothesis is proven to be false, the null hypothesis is considered to be true. Usually a null hypothesis shows no direct correlation between the defined variables.
Here are some of the examples
- The consumption of herbal tea has no effect on sleep quality. (This hypothesis assumes that herbal tea consumption does not impact the quality of sleep.)
- The number of hours spent playing video games is unrelated to academic performance. (Here, the null hypothesis suggests that no relationship exists between video gameplay duration and academic achievement.)
- Implementing flexible work schedules has no influence on employee job satisfaction. (This hypothesis contends that providing flexible schedules does not affect how satisfied employees are with their jobs.)
- Writing ability of a 7th grader is not affected by reading editorial example. ( There is no relationship between reading an editorial example and improving a 7th grader’s writing abilities.)
- The type of lighting in a room does not affect people’s mood. (In this null hypothesis, there is no connection between the kind of lighting in a room and the mood of those present.)
- The use of social media during break time does not impact productivity at work. (This hypothesis proposes that social media usage during breaks has no effect on work productivity.)
As you learn how to write a hypothesis, remember that aiming for clarity, testability, and relevance to your research question is vital. By mastering this skill, you’re well on your way to conducting impactful scientific research. Good luck!
Importance of a Hypothesis in Research
A well-structured hypothesis is a vital part of any research project for several reasons:
- It provides clear direction for the study by setting its focus and purpose.
- It outlines expectations of the research, making it easier to measure results.
- It helps identify any potential limitations in the study, allowing researchers to refine their approach.
In conclusion, a hypothesis plays a fundamental role in the research process. By understanding its concept and constructing a well-thought-out hypothesis, researchers lay the groundwork for a successful, scientifically sound investigation.
How to Write a Hypothesis?
Here are five steps that you can follow to write an effective hypothesis.
Step 1: Identify Your Research Question
The first step in learning how to compose a hypothesis is to clearly define your research question. This question is the central focus of your study and will help you determine the direction of your hypothesis.
Step 2: Determine the Variables
When exploring how to write a hypothesis, it’s crucial to identify the variables involved in your study. You’ll need at least two variables:
- Independent variable : The factor you manipulate or change in your experiment.
- Dependent variable : The outcome or result you observe or measure, which is influenced by the independent variable.
Step 3: Build the Hypothetical Relationship
In understanding how to compose a hypothesis, constructing the relationship between the variables is key. Based on your research question and variables, predict the expected outcome or connection. This prediction should be specific, testable, and, if possible, expressed in the “If…then” format.
Step 4: Write the Null Hypothesis
When mastering how to write a hypothesis, it’s important to create a null hypothesis as well. The null hypothesis assumes no relationship or effect between the variables, acting as a counterpoint to your primary hypothesis.
Step 5: Review Your Hypothesis
Finally, when learning how to compose a hypothesis, it’s essential to review your hypothesis for clarity, testability, and relevance to your research question. Make any necessary adjustments to ensure it provides a solid basis for your study.
In conclusion, understanding how to write a hypothesis is crucial for conducting successful scientific research. By focusing on your research question and carefully building relationships between variables, you will lay a strong foundation for advancing research and knowledge in your field.
Hypothesis vs. Prediction: What’s the Difference?
Understanding the differences between a hypothesis and a prediction is crucial in scientific research. Often, these terms are used interchangeably, but they have distinct meanings and functions. This segment aims to clarify these differences and explain how to compose a hypothesis correctly, helping you improve the quality of your research projects.
Hypothesis: The Foundation of Your Research
A hypothesis is an educated guess about the relationship between two or more variables. It provides the basis for your research question and is a starting point for an experiment or observational study.
The critical elements for a hypothesis include:
- Specificity: A clear and concise statement that describes the relationship between variables.
- Testability: The ability to test the hypothesis through experimentation or observation.
To learn how to write a hypothesis, it’s essential to identify your research question first and then predict the relationship between the variables.
Prediction: The Expected Outcome
A prediction is a statement about a specific outcome you expect to see in your experiment or observational study. It’s derived from the hypothesis and provides a measurable way to test the relationship between variables.
Here’s an example of how to write a hypothesis and a related prediction:
- Hypothesis: Consuming a high-sugar diet leads to weight gain.
- Prediction: People who consume a high-sugar diet for six weeks will gain more weight than those who maintain a low-sugar diet during the same period.
Key Differences Between a Hypothesis and a Prediction
While a hypothesis and prediction are both essential components of scientific research, there are some key differences to keep in mind:
- A hypothesis is an educated guess that suggests a relationship between variables, while a prediction is a specific and measurable outcome based on that hypothesis.
- A hypothesis can give rise to multiple experiment or observational study predictions.
To conclude, understanding the differences between a hypothesis and a prediction, and learning how to write a hypothesis, are essential steps to form a robust foundation for your research. By creating clear, testable hypotheses along with specific, measurable predictions, you lay the groundwork for scientifically sound investigations.
Here’s a wrap-up for this guide on how to write a hypothesis. We’re confident this article was helpful for many of you. We understand that many students struggle with writing their school research . However, we hope to continue assisting you through our blog tutorial on writing different aspects of academic assignments.
For further information, you can check out our reverent blog or contact our professionals to avail amazing writing services. Paper perk experts tailor assignments to reflect your unique voice and perspectives. Our professionals make sure to stick around till your satisfaction. So what are you waiting for? Pick your required service and order away!
How to write a good hypothesis?
How to write a hypothesis in science, how to write a research hypothesis, how to write a null hypothesis, what is the format for a scientific hypothesis, how do you structure a proper hypothesis, can you provide an example of a hypothesis, what is the ideal hypothesis structure.
The ideal hypothesis structure includes the following;
- A clear statement of the relationship between variables.
- testable prediction.
- falsifiability.
If your hypothesis has all of these, it is both scientifically sound and effective.
How to write a hypothesis for product management?
Writing a hypothesis for product management involves a simple process:
- First, identify the problem or question you want to address.
- State your assumption or belief about the solution to that problem. .
- Make a hypothesis by predicting a specific outcome based on your assumption.
- Make sure your hypothesis is specific, measurable, and testable.
- Use experiments, data analysis, or user feedback to validate your hypothesis.
- Make informed decisions for product improvement.
Following these steps will help you in effectively formulating hypotheses for product management.
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Research Hypothesis In Psychology: Types, & Examples
Saul Mcleod, PhD
Editor-in-Chief for Simply Psychology
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.
Learn about our Editorial Process
Olivia Guy-Evans, MSc
Associate Editor for Simply Psychology
BSc (Hons) Psychology, MSc Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
On This Page:
A research hypothesis, in its plural form “hypotheses,” is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method .
Hypotheses connect theory to data and guide the research process towards expanding scientific understanding
Some key points about hypotheses:
- A hypothesis expresses an expected pattern or relationship. It connects the variables under investigation.
- It is stated in clear, precise terms before any data collection or analysis occurs. This makes the hypothesis testable.
- A hypothesis must be falsifiable. It should be possible, even if unlikely in practice, to collect data that disconfirms rather than supports the hypothesis.
- Hypotheses guide research. Scientists design studies to explicitly evaluate hypotheses about how nature works.
- For a hypothesis to be valid, it must be testable against empirical evidence. The evidence can then confirm or disprove the testable predictions.
- Hypotheses are informed by background knowledge and observation, but go beyond what is already known to propose an explanation of how or why something occurs.
Predictions typically arise from a thorough knowledge of the research literature, curiosity about real-world problems or implications, and integrating this to advance theory. They build on existing literature while providing new insight.
Types of Research Hypotheses
Alternative hypothesis.
The research hypothesis is often called the alternative or experimental hypothesis in experimental research.
It typically suggests a potential relationship between two key variables: the independent variable, which the researcher manipulates, and the dependent variable, which is measured based on those changes.
The alternative hypothesis states a relationship exists between the two variables being studied (one variable affects the other).
A hypothesis is a testable statement or prediction about the relationship between two or more variables. It is a key component of the scientific method. Some key points about hypotheses:
- Important hypotheses lead to predictions that can be tested empirically. The evidence can then confirm or disprove the testable predictions.
In summary, a hypothesis is a precise, testable statement of what researchers expect to happen in a study and why. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.
An experimental hypothesis predicts what change(s) will occur in the dependent variable when the independent variable is manipulated.
It states that the results are not due to chance and are significant in supporting the theory being investigated.
The alternative hypothesis can be directional, indicating a specific direction of the effect, or non-directional, suggesting a difference without specifying its nature. It’s what researchers aim to support or demonstrate through their study.
Null Hypothesis
The null hypothesis states no relationship exists between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to manipulating the independent variable.
It states results are due to chance and are not significant in supporting the idea being investigated.
The null hypothesis, positing no effect or relationship, is a foundational contrast to the research hypothesis in scientific inquiry. It establishes a baseline for statistical testing, promoting objectivity by initiating research from a neutral stance.
Many statistical methods are tailored to test the null hypothesis, determining the likelihood of observed results if no true effect exists.
This dual-hypothesis approach provides clarity, ensuring that research intentions are explicit, and fosters consistency across scientific studies, enhancing the standardization and interpretability of research outcomes.
Nondirectional Hypothesis
A non-directional hypothesis, also known as a two-tailed hypothesis, predicts that there is a difference or relationship between two variables but does not specify the direction of this relationship.
It merely indicates that a change or effect will occur without predicting which group will have higher or lower values.
For example, “There is a difference in performance between Group A and Group B” is a non-directional hypothesis.
Directional Hypothesis
A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place. (i.e., greater, smaller, less, more)
It specifies whether one variable is greater, lesser, or different from another, rather than just indicating that there’s a difference without specifying its nature.
For example, “Exercise increases weight loss” is a directional hypothesis.
![Research Hypothesis In Psychology: Types, & Examples 1 hypothesis](https://www.simplypsychology.org/wp-content/uploads/hypothesis.jpg)
Falsifiability
The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory or hypothesis to be considered scientific, it must be testable and irrefutable.
Falsifiability emphasizes that scientific claims shouldn’t just be confirmable but should also have the potential to be proven wrong.
It means that there should exist some potential evidence or experiment that could prove the proposition false.
However many confirming instances exist for a theory, it only takes one counter observation to falsify it. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.
For Popper, science should attempt to disprove a theory rather than attempt to continually provide evidence to support a research hypothesis.
Can a Hypothesis be Proven?
Hypotheses make probabilistic predictions. They state the expected outcome if a particular relationship exists. However, a study result supporting a hypothesis does not definitively prove it is true.
All studies have limitations. There may be unknown confounding factors or issues that limit the certainty of conclusions. Additional studies may yield different results.
In science, hypotheses can realistically only be supported with some degree of confidence, not proven. The process of science is to incrementally accumulate evidence for and against hypothesized relationships in an ongoing pursuit of better models and explanations that best fit the empirical data. But hypotheses remain open to revision and rejection if that is where the evidence leads.
- Disproving a hypothesis is definitive. Solid disconfirmatory evidence will falsify a hypothesis and require altering or discarding it based on the evidence.
- However, confirming evidence is always open to revision. Other explanations may account for the same results, and additional or contradictory evidence may emerge over time.
We can never 100% prove the alternative hypothesis. Instead, we see if we can disprove, or reject the null hypothesis.
If we reject the null hypothesis, this doesn’t mean that our alternative hypothesis is correct but does support the alternative/experimental hypothesis.
Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct. We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.
How to Write a Hypothesis
- Identify variables . The researcher manipulates the independent variable and the dependent variable is the measured outcome.
- Operationalized the variables being investigated . Operationalization of a hypothesis refers to the process of making the variables physically measurable or testable, e.g. if you are about to study aggression, you might count the number of punches given by participants.
- Decide on a direction for your prediction . If there is evidence in the literature to support a specific effect of the independent variable on the dependent variable, write a directional (one-tailed) hypothesis. If there are limited or ambiguous findings in the literature regarding the effect of the independent variable on the dependent variable, write a non-directional (two-tailed) hypothesis.
- Make it Testable : Ensure your hypothesis can be tested through experimentation or observation. It should be possible to prove it false (principle of falsifiability).
- Clear & concise language . A strong hypothesis is concise (typically one to two sentences long), and formulated using clear and straightforward language, ensuring it’s easily understood and testable.
Consider a hypothesis many teachers might subscribe to: students work better on Monday morning than on Friday afternoon (IV=Day, DV= Standard of work).
Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and a Friday afternoon and then measuring their immediate recall of the material covered in each session, we would end up with the following:
- The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
- The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.
More Examples
- Memory : Participants exposed to classical music during study sessions will recall more items from a list than those who studied in silence.
- Social Psychology : Individuals who frequently engage in social media use will report higher levels of perceived social isolation compared to those who use it infrequently.
- Developmental Psychology : Children who engage in regular imaginative play have better problem-solving skills than those who don’t.
- Clinical Psychology : Cognitive-behavioral therapy will be more effective in reducing symptoms of anxiety over a 6-month period compared to traditional talk therapy.
- Cognitive Psychology : Individuals who multitask between various electronic devices will have shorter attention spans on focused tasks than those who single-task.
- Health Psychology : Patients who practice mindfulness meditation will experience lower levels of chronic pain compared to those who don’t meditate.
- Organizational Psychology : Employees in open-plan offices will report higher levels of stress than those in private offices.
- Behavioral Psychology : Rats rewarded with food after pressing a lever will press it more frequently than rats who receive no reward.
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Hypothesis Testing | A Step-by-Step Guide with Easy Examples
Published on November 8, 2019 by Rebecca Bevans . Revised on June 22, 2023.
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics . It is most often used by scientists to test specific predictions, called hypotheses, that arise from theories.
There are 5 main steps in hypothesis testing:
- State your research hypothesis as a null hypothesis and alternate hypothesis (H o ) and (H a or H 1 ).
- Collect data in a way designed to test the hypothesis.
- Perform an appropriate statistical test .
- Decide whether to reject or fail to reject your null hypothesis.
- Present the findings in your results and discussion section.
Though the specific details might vary, the procedure you will use when testing a hypothesis will always follow some version of these steps.
Table of contents
Step 1: state your null and alternate hypothesis, step 2: collect data, step 3: perform a statistical test, step 4: decide whether to reject or fail to reject your null hypothesis, step 5: present your findings, other interesting articles, frequently asked questions about hypothesis testing.
After developing your initial research hypothesis (the prediction that you want to investigate), it is important to restate it as a null (H o ) and alternate (H a ) hypothesis so that you can test it mathematically.
The alternate hypothesis is usually your initial hypothesis that predicts a relationship between variables. The null hypothesis is a prediction of no relationship between the variables you are interested in.
- H 0 : Men are, on average, not taller than women. H a : Men are, on average, taller than women.
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For a statistical test to be valid , it is important to perform sampling and collect data in a way that is designed to test your hypothesis. If your data are not representative, then you cannot make statistical inferences about the population you are interested in.
There are a variety of statistical tests available, but they are all based on the comparison of within-group variance (how spread out the data is within a category) versus between-group variance (how different the categories are from one another).
If the between-group variance is large enough that there is little or no overlap between groups, then your statistical test will reflect that by showing a low p -value . This means it is unlikely that the differences between these groups came about by chance.
Alternatively, if there is high within-group variance and low between-group variance, then your statistical test will reflect that with a high p -value. This means it is likely that any difference you measure between groups is due to chance.
Your choice of statistical test will be based on the type of variables and the level of measurement of your collected data .
- an estimate of the difference in average height between the two groups.
- a p -value showing how likely you are to see this difference if the null hypothesis of no difference is true.
Based on the outcome of your statistical test, you will have to decide whether to reject or fail to reject your null hypothesis.
In most cases you will use the p -value generated by your statistical test to guide your decision. And in most cases, your predetermined level of significance for rejecting the null hypothesis will be 0.05 – that is, when there is a less than 5% chance that you would see these results if the null hypothesis were true.
In some cases, researchers choose a more conservative level of significance, such as 0.01 (1%). This minimizes the risk of incorrectly rejecting the null hypothesis ( Type I error ).
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The results of hypothesis testing will be presented in the results and discussion sections of your research paper , dissertation or thesis .
In the results section you should give a brief summary of the data and a summary of the results of your statistical test (for example, the estimated difference between group means and associated p -value). In the discussion , you can discuss whether your initial hypothesis was supported by your results or not.
In the formal language of hypothesis testing, we talk about rejecting or failing to reject the null hypothesis. You will probably be asked to do this in your statistics assignments.
However, when presenting research results in academic papers we rarely talk this way. Instead, we go back to our alternate hypothesis (in this case, the hypothesis that men are on average taller than women) and state whether the result of our test did or did not support the alternate hypothesis.
If your null hypothesis was rejected, this result is interpreted as “supported the alternate hypothesis.”
These are superficial differences; you can see that they mean the same thing.
You might notice that we don’t say that we reject or fail to reject the alternate hypothesis . This is because hypothesis testing is not designed to prove or disprove anything. It is only designed to test whether a pattern we measure could have arisen spuriously, or by chance.
If we reject the null hypothesis based on our research (i.e., we find that it is unlikely that the pattern arose by chance), then we can say our test lends support to our hypothesis . But if the pattern does not pass our decision rule, meaning that it could have arisen by chance, then we say the test is inconsistent with our hypothesis .
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
- Normal distribution
- Descriptive statistics
- Measures of central tendency
- Correlation coefficient
Methodology
- Cluster sampling
- Stratified sampling
- Types of interviews
- Cohort study
- Thematic analysis
Research bias
- Implicit bias
- Cognitive bias
- Survivorship bias
- Availability heuristic
- Nonresponse bias
- Regression to the mean
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.
A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).
Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.
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How to Write a Hypothesis for a Research Paper: Best Hacks and Examples
Updated 27 Jun 2024
The narrative of a research study commences with the formulation of a question. Inquisitive researchers worldwide are constantly posing questions and crafting research hypotheses. The effectiveness of a paper’s conclusion hinges on the quality of every research element. From this guide, you’ll learn how to write a hypothesis for a research paper and find examples that can assist you in grasping the process of crafting a strong text. We aim to clarify the definition and characteristics of a research hypothesis and guide researchers in formulating one effectively. Writing a clear and testable hypothesis is crucial for any research project, and if you're struggling, you might consider the option to pay for essay services to ensure your hypothesis is well-formulated and precise.
What is a research hypothesis?
It is a tentative answer to a research question that has not been tested yet. It should be based on established theories and knowledge and be testable through scientific methods like experiments and data analysis.
To understand a hypothesis definition and its purpose, one must analyze a scientist's steps when doing research. To address a particular issue, the initial step involves identifying the research question, conducting a preliminary study, and then proceeding to answer the question by conducting experiments and analyzing the observed outcomes. Still, before embarking on the experimental phase, it’s essential to determine the expected results. At this stage, researchers make an informed estimation and formulate a supposition that they aim to confirm or disprove throughout their study.
The essential characteristics of a hypothesis
Now that you have a brief understanding of what a hypothesis in a research paper is, let’s examine its key defining characteristics that contribute to its effectiveness:
- Clear and specific: A good hypothesis is clear, concise, and specific in its formulation. It precisely states the relationship or expected outcome being investigated.
- Testable: It is testable, meaning it can be empirically examined through observations, experiments, or data analysis. Gathering evidence to support or refute the researcher’s guess should be possible.
- Grounded in existing knowledge: A good hypothesis in a research paper is based on existing theories, concepts, or empirical evidence. It demonstrates a solid understanding of the relevant literature and builds upon prior knowledge in the field.
- Falsifiable: It can be potentially proven false. This characteristic allows obtaining data that contradicts the primary assumption, enabling meaningful scientific inquiry.
- Logical and plausible: A supposition in research is logically reasoned and plausible. It should align with known facts and be supported by sound reasoning and evidence.
- Relevant and significant: It addresses a meaningful research question and has implications for the field. It should contribute to the existing knowledge base and have practical or theoretical significance.
- Limited in scope: It is focused and limited in scope. It should address a specific aspect or relationship rather than attempting to explain or predict everything in a broad context.
By embodying these characteristics, a good hypothesis provides a solid foundation for research, guiding the study’s design, data collection, and analysis, ultimately contributing to the generation of valuable scientific knowledge.
What are the sources for building a hypothesis?
There are several potential sources for developing a good research paper hypothesis. Let’s consider their details and examples:
- Scientific theories
Hypotheses can stem from existing scientific theories. Suppose we have an established theory in psychology that suggests a positive correlation between sleep quality and cognitive performance. Based on this theory, we can create a statement:
“If individuals experience better sleep quality, then their cognitive performance will improve compared to those with poorer sleep quality.”
- Previous studies and experiences
Observations from past studies and current experiences can contribute to formulating suppositions. Let’s say previous studies have shown that a particular herb has anti-inflammatory properties. Building upon this finding, we can formulate the following:
“If individuals consume the herb extract, then their inflammation levels will decrease compared to a control group.”
- Similarities among phenomena
Resemblances between different phenomena can inspire hypotheses. Consider a study investigating the effects of exercise on mood. Drawing an analogy from previous research showing that outdoor nature exposure improves mood, a scientist can formulate a guess:
“If individuals engage in outdoor exercise, then their mood will improve compared to those engaging in indoor exercise.”
- Empirical observations
Direct observations of phenomena or patterns in the real world can spark the development of ideas. Suppose a researcher observes that learners who study in a quiet environment tend to perform better on exams. This observation can lead to the next statement:
“If learners study in a quiet environment, then their exam scores will be higher compared to those who study in a noisy environment.”
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Types of research hypotheses
They can be classified into one or more of the seven primary categories, depending on the nature of your investigation, a chosen research methodology , and anticipated findings. These categories are not mutually exclusive, meaning a single supposition can belong to multiple types.
- A simple hypothesis is based on the relationship between two variables: one independent and one dependent. Let’s see a hypothesis example:
“Increased study time leads to improved test scores.”
- A complex approach involves the relationship between numerous variables (more than two), e.g., two dependent variables and one independent, or vice versa.
“Both exercise frequency and diet quality have a combined effect on weight loss.”
- A null hypothesis suggests no relationship between variables.
“There is no significant difference in anxiety levels between Group A and Group B.”
- An alternative hypothesis is used alongside a null one, stating the opposite and asserting that only one of the two ideas can be true.
“The new drug treatment reduces symptoms of depression more effectively than the current standard treatment.”
- A logical approach relies on a relationship between variables based on reasoning or deduction, lacking actual data or evidence.
“If students receive regular feedback on their assignments, their academic performance will improve.”
- An empirical (“working”) hypothesis is currently being tested and relies on concrete data.
“Increasing the temperature will accelerate the rate of the chemical reaction.”
- A statistical approach involves testing a population sample and using statistical evidence to conclude about the whole population. This method tests only a portion of the population and generalizes based on existing data.
“Based on the sample data, there is a significant correlation between sleep duration and memory retention in the population.”
How to write a hypothesis for a research paper step-by-step
- Search for answers to your questions. Start by questioning the world around you, exploring why things are the way they are and what causes the phenomena you observe. Follow your curiosity and choose a research topic that genuinely interests you.
- Do preliminary research. Gather background information for your outline, depending on the scope of your research. This may involve reading books or performing quick web searches. Focus on gathering the necessary information to prove or disprove your idea.
- Determine variables. Define the independent and dependent variables for your research. Consider the factors you have control over and ensure they align with your experiment’s limitations.
- Formulate an if-then statement. Create your guess using an if-then format, illustrating the cause-and-effect relationship you intend to test. For example, “If we do morning exercise, then we’ll be healthier.”
- Gather supportive data. Conduct experiments to gather data that maintains your idea. Remember, even if your research disproves your supposition, it contributes to the scientific process.
- Write confidently. Finally, document your findings in your work for others to access. Writing a thesis requires distinct skills separate from conducting experiments.
Tips on creating a flawless research paper hypothesis
- Be realistic and feasible: Consider the practicality and limitations of your study. Ensure that your hypothesis is realistic and can be tested within the constraints of your available resources, time, and ethical considerations.
- Avoid value judgments: Be neutral and objective. Avoid including personal beliefs, value judgments, or subjective opinions. Stick to empirical statements based on evidence.
- Be concise: Aim for a concise and focused hypothesis. Avoid unnecessary complexity or unnecessary elaboration. Ensure it is succinctly stated in a single or a few sentences.
- Revise and refine: Continuously revise and refine your content as you gather more information and insights throughout your research process. Be open to modifying or adjusting your hypothesis based on new evidence or unexpected findings.
Some examples to inspire you
By following our guide and tips, you can easily create well-formed hypotheses. To help you get started, we have curated a list of research questions and relevant hypothesis examples.
Research question: Does regular exercise improve cognitive function in older adults?
Hypothesis: If older adults exercise regularly, their cognitive function will improve compared to sedentary ones.
Null hypothesis : No significant difference in cognitive function exists between older adults who exercise regularly and those who lead a sedentary lifestyle.
Research question: Does caffeine consumption affect sleep quality?
Hypothesis: If individuals consume high amounts of caffeine before bedtime, their sleep quality will be negatively impacted compared to those who consume low or no caffeine.
Null hypothesis : There is no significant difference in sleep quality between individuals who consume high amounts of caffeine before bedtime and those who consume low or no caffeine.
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Steven Robinson is an academic writing expert with a degree in English literature. His expertise, patient approach, and support empower students to express ideas clearly. On EduBirdie's blog, he provides valuable writing guides on essays, research papers, and other intriguing topics. Enjoys chess in free time.
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How To Write a Strong Research Hypothesis
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Are you looking to take your research project to the next level? Have you heard of the power of a hypothesis but need to figure out how to formulate one that will unlock potential discoveries? We can help!
So get ready; it's time to dive into unlocking the power of research! This blog post will explore what makes a well-crafted and powerful hypothesis - from identifying a research question to developing supporting evidence.
By learning how to craft a compelling hypothesis, you'll have more tremendous success in every step of your research project.
What are hypotheses, and why are they important?
A hypothesis is an educated guess or a proposition based on limited evidence as a starting point for further investigation. It provides a framework for research and allows researchers to refine their ideas, collect data, and draw conclusions. Hypotheses are essential to the process because they will enable us to organize our thoughts and test theories properly.
Hypotheses are used in many fields , from medicine to psychology to economics. In each area, developing hypotheses based on observations enable researchers to make predictions about their data and guide them toward finding meaningful results.
For example, in medicine, hypotheses can be used to predict which treatments will be most effective for particular conditions or which drugs may have adverse effects when taken together. This allows doctors to make better decisions when caring for patients.
In psychology, hypotheses are often used in experiments to determine whether certain variables influence behavior or mental processes. By testing different combinations of variables, psychologists can identify patterns and understand why people behave the way they do.
In economics, hypotheses provide economists with a framework for analyzing the relationship between economic variables such as wages and consumer spending habits. By understanding these relationships, economists can better understand how economic forces affect the economy.
Overall, hypotheses play an essential role in helping scientists develop new ideas and draw meaningful conclusions from the collected data. Without taking the step to create hypotheses, it would be difficult for researchers to make sense of the vast amounts of information available today and use it effectively in their investigations.
How to determine an effective research question to form your hypothesis
When conducting research, having a compelling research question is critical . Properly formulating this question will allow the researcher to develop their hypothesis. A research question provides a clear and focused goal for your research study and also gives direction on how to get there. A compelling research question should be specific, answerable in the context of your field of study, significant, novel (not already answered by previous studies), and timely – that is, relevant to current events or trends.
Before determining the best research question, you must first understand your topic. Think about the area of knowledge that interests you most and narrow it down to a single theme or concept within this topic. Focus on what interests you most within this theme, and make sure there is room for further exploration and analysis. Once you have chosen a specific topic and narrowed down your focus, you can begin formulating questions related to your project.
To ensure relevance and impact to your field of study, choose questions that address essential issues in the literature or suggest solutions to existing problems. Avoid overly broad topics with unclear objectives; instead, opt for focused questions to enable targeted data collection and analysis with concrete results.
Additionally, consider time frames when formulating questions. If the issue has been discussed extensively in the past but has not been revisited recently, then it's likely not worthy of a new investigation.
Once you have developed some potential questions related to your topic, review them carefully and decide which question best captures the essence of what you want to learn through researching this topic.
Ask yourself:
- Is this question answerable?
- Does it fit within my field of study?
- Is it significant enough?
- Would its findings be novel?
If so, then congratulations! You have identified a compelling research question.
Tips for crafting a well-crafted hypothesis
Once you have formulated the official research question, you may develop the formal hypothesis. When composing a hypothesis, it's essential to think carefully about the question you are trying to answer.
A solid hypothesis should be testable, meaning that it can be verified or disproved through research. It should also be specific and focused on one issue at a time. Here are some tips for crafting a well-crafted hypothesis:
- Consider the goal of your research: Think about what it is that you want to learn or determine from your experiment and make sure that your hypothesis reflects this goal.
- Create an educated guess as to why something is happening: Your hypothesis should explain why something is occurring based on what evidence you already have and direct further investigation into the matter. For example, if you hypothesize that increased carbon dioxide levels in the atmosphere will lead to global warming, your research should focus on examining this relationship further.
- Define any variables or parameters involved in the experiment: This includes things like temperature or chemical composition that could potentially affect the outcome of any experiments done in pursuit of testing your hypothesis.
- Use clear and precise language: Make sure your hypothesis is written with clear and precise language so that anyone reading it can understand exactly what you are attempting to investigate or explain. Avoid complex words and keep sentences short whenever possible.
Following these simple tips will help ensure that your hypothesis is well-crafted and ready for testing!
Examples of evidence that can support your hypothesis
When it comes to developing a hypothesis, supporting evidence is essential for making sure it holds up. This evidence helps strengthen the argument that is being driven by providing facts and logical reasoning that support the hypothesis.
Examples of evidence that can be used to back up a hypothesis include using data from experiments, case studies, and other research projects. Data from experiments can provide insight into how certain variables interact to form a particular outcome.
Case studies may offer greater depth in understanding a specific phenomenon's cause and effect; research projects may yield results that confirm or refute existing theories on a subject.
In addition to these traditional forms of evidence, personal experiences or observations can also help to support a hypothesis. For example, if someone's daily commute has been consistently faster since they changed routes, they could use their personal experience to argue that making this change resulted in shorter commutes.
Similarly, suppose someone has witnessed how two variables consistently coincide (i.e., when one goes up, another goes down). In that case, this could be used to support the notion that there is some correlation between these two aspects.
Overall, evidence to support your hypothesis is crucial for ensuring its validity and credibility. While conducting experiments or researching may seem like time-consuming processes, having solid supporting evidence will make it much easier to defend your ideas convincingly when challenged.
Therefore, it is crucial to take the time necessary to gather credible sources of information to provide the most substantial possible backing for your hypotheses.
Understanding the potential of hypotheses and how they can help your research project progress
The power of research lies in the ability to develop and test hypotheses. A hypothesis is a statement or an idea that can be tested to determine its validity.
Essentially, it is a form of educated guesswork that helps researchers form conclusions about their data. By developing a hypothesis for a research project, you are effectively setting up the framework for further exploration.
When developing a hypothesis, you must consider both the expected outcomes and possible alternative explanations. This will help you focus on testing the possible results without getting sidetracked by irrelevant information. Once you have established a concrete hypothesis, it can then be used as a basis for further research and experimentation.
The process of testing hypotheses is an integral part of the scientific method and can help researchers build confidence in their findings and conclusions. Through careful observation and experimentation, researchers can compare their results against what they initially hypothesized, allowing them to draw more accurate conclusions about their data. As such, hypotheses play an essential role in helping researchers connect the dots between different pieces of evidence and form meaningful conclusions.
Overall, understanding how hypotheses can be used in research projects can be immensely beneficial in helping progress towards reaching meaningful insights from their data. By setting up expectations ahead of time and then testing them against real-world conditions, researchers can gain valuable insights that could potentially change the way we understand our world – now that's something worth exploring!
Final thoughts
A hypothesis is a proposed explanation for an observable phenomenon. It's important to note that hypotheses are not the same thing as theories–a theory is a much broader and well-established frame of reference that explains multiple phenomena.
Generally, scientists form a research question and then narrow it down to a testable hypothesis. After making observations and conducting experiments to gather data, researchers can use evidence to support or reject the hypothesis.
By following these steps to formulate a solid hypothesis, you will be on your way to developing a successful research project. Happy researching!
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MINNEAPOLIS / ST. PAUL (7/18/2024) – Seven graduate students advised by Department of Chemistry faculty members were recently awarded the University of Minnesota’s Doctoral Dissertation Fellowship. The seven students honored by this prestigious award are Kaylee Barr, Brylon Denman, Madeline Honig, Chris Seong, Sneha Venkatachalapathy, Murphi Williams, and Caini Zheng.
Kaylee Barr , a Chemical Engineering and Materials Science PhD student, is entering her fifth year in the Reineke Group . Before making the move to Minnesota, she received her BS in Chemical Engineering from the University of Kansas. “I came to the University of Minnesota because of the department's developments in polymer science, and because I was interested in the intersection of polymer science and drug delivery in Theresa Reineke's lab,” she says. Here at UMN, Kaylee studies how bottlebrush polymer architecture affects pH-responsive oral drug delivery. This summer, she is excited to grow professionally and as a scientist in an intern position at Genentech.
Brylon Denman is a Chemistry PhD candidate in the Roberts Group . She joined the UMN community in 2020 after completing her BS in Biochemistry at St. Louis University. “My research in the Roberts group seeks to resolve regioselectivity and reactivity issues within aryne methodology via ligand control,” Brylon says. “To accomplish this task, I have taken a mechanistic and hypothesis driven approach to understand how key molecular parameters modify regioselectivity and reactivity. I hope to use the knowledge I have gained from these studies to both improve the synthetic utility of aryne intermediates, and improve the sustainability of aryne reactions.” Brylon is also passionate about sustainable and green chemistry. As a founding member of the Sustainable and Green Chemistry committee, Brylon strives to collaborate with other department teammates to strengthen the culture of green and sustainable chemistry through integration into teaching, research, and community engagement. “In my career I aim to continue this advocacy and use my breadth of knowledge to enact sustainable change at a major pharmaceutical company as emphasizing sustainability on such a large scale can lead to a large impact,” she says. As she works through her internship at AbbVie this summer, Brylon is looking towards the future to outline her next steps after graduation.
Madeline Honig first experienced Chemistry at UMN during a summer REU experience in the Bühlmann Lab . She formally joined the Prof. Bühlmann's team in Fall 2020 after earning her BA in Chemistry from Earlham College. Her research here at UMN has focused on the development and improved understanding of polymeric membrane-based ion-selective electrodes (ISEs). “One of my projects involves developing a quantitative parameter to better define the upper detection limits of these sensors which can be used to more accurately define sensor performance and predict the working range under different conditions,” Madeline says. “This research led us to investigate the unexplained 'super-Nernstian' responses of some pH-selective electrodes and expand the phase boundary model (the quantitative model that predicts ISE behavior) to include the formation of complexes between protonated ionophores and counter-ions in the sensing membrane. ISEs have been widely used for decades in clinical blood analysis among many other applications so it's exciting that I was still able to add to our fundamental understanding of how these sensors function.” One of Madeline’s goals is to use her research to enable the development of improved sensors that can be used in a wider range of conditions. Over the course of her graduate studies, Madeline has had the opportunity to be a graduate student mentor for two other students: Ariki Haba, a visiting master's student from Japan, and Katie O'Leary, a summer REU student, who both made significant contributions to the project. “Acting as a graduate mentor was really cool and I hope I can also make graduate-level chemistry research more approachable for everyone that I work with,” Madeline says. For her significant research efforts, Madeline was also recently selected in a national competition as one of the four winners of the 2024 Eastern Analytical Symposium Graduate Student Research Award. She will accept the award in November in Plainsboro NJ at the Eastern Analytical Symposium.
Chris Seong , an international student from New Zealand and PhD candidate in the Roberts Group, came to UMN after completing his BA with Distinction in Chemistry at St. Olaf College in 2020. Chris’ overarching chemistry interests involve the development of methods to utilize naturally abundant carboxylic acids as feedstock to synthesize medicinally relevant products, which are traditionally made with non-renewable starting materials derived from fossil fuels. “My earlier work has been focused on making alkyl-alkyl bonds through decarboxylation, but lately, in true Roberts Group fashion, I have turned my attention to using a similar mechanism to do aryne chemistry,” Chris says. He is currently working to publish a paper on the aryne project that he has been working on with two talented group mates; Sal Kargbo and Felicia Yu. “I am really excited to share this cool chemistry with the world,” he says. Outside of the lab, Chris is working on expanding his network to apply for jobs in the pharmaceutical industry – specifically in the early process space.
Sneha Venkatachalapathy is a member of the Distefano Group and an international student from India. She completed her BS in Chemistry with a minor degree in Biotechnology from Shiv Nadar University, Greater Noida, India in 2020. “Chemistry has always been my passion since high school. I still remember my first successful brown ring test that has left a remarkable fascination and interest towards chemistry,” Sneha says. “This early fascination has driven my academic journey, guided by mentors like Dr. Subhabrata Sen, who encouraged me to pursue a PhD in the United States.” Sneha was drawn towards working in the Chemical Biology research field where she could directly contribute to developing human life. “Joining Dr. Mark Distefano’s lab at UMN provided me with the chance to collaborate with Dr. Mohammad Rashidian from Dana Farber Cancer Institute. Together, we work towards expanding the scope of protein prenylation to construct protein-based cancer diagnostic tools,” she says. Sneha’s goal for her time in the UMN PhD program is to create innovative protein-based tools for cancer detection and treatment, aiming to enhance patient’s quality of life. She says she is looking forward to continuing to develop her leadership skills as she continues her doctorate, and is also exploring future opportunities beyond UMN. “One thing that motivates me daily is the belief that my research contributions to the scientific community would enhance our understanding of cancer diagnostic methods, ultimately leading to improved patient outcomes worldwide,” she says.
Murphi Williams completed her undergraduate studies at the University of Wisconsin-Eau Claire, then joined the Bhagi-Damodaran at UMN in 2020. When it comes to research, Murphi is interested in chemical biology, more specifically, looking into proteins involved in important biological problems. “One of my major projects is developing and characterizing a potential inhibitor for Mycobacterium tuberculosis , the bacteria that causes tuberculosis,” Murphi says. “Tuberculosis is the leading infectious disease so my projects center on understanding and inhibiting heme proteins important for the bacteria. Specifically, a previous lab member identified a small molecule that I've been characterizing the activity of in cells.” Her current research goal is to express and purify the protein targets for her small molecule inhibitor in the lab to further demonstrate the in vitro activity. She is also contemplating a future career in science communication. Outside of the lab, she enjoys working on her garden.
Caini Zheng joined the Chemistry at the UMN in 2019 after finishing her undergraduate studies at Shanghai Jiao Tong University. She is currently a sixth-year graduate student co-advised by Profs. Tim Lodge and Ilja Siepmann . Her research focuses on the phase behavior of soft materials, including polymers and oligomers. Her DDF statement is titled "Self-Assembly of Polymers and Amphiphiles into Bicontinuous Phases". Caini is currently working on a project to elucidate the self-assembly of glycolipids through molecular dynamics simulations coupled with machine learning methods. In the future, she wants to work in the industry on bridging data science with traditional material research.
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Developing a hypothesis (with example) Step 1. Ask a question. Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project. Example: Research question.
It seeks to explore and understand a particular aspect of the research subject. In contrast, a research hypothesis is a specific statement or prediction that suggests an expected relationship between variables. It is formulated based on existing knowledge or theories and guides the research design and data analysis. 7.
3. Simple hypothesis. A simple hypothesis is a statement made to reflect the relation between exactly two variables. One independent and one dependent. Consider the example, "Smoking is a prominent cause of lung cancer." The dependent variable, lung cancer, is dependent on the independent variable, smoking. 4.
The first step in formulating a hypothesis is to clearly identify the research problem. This involves understanding the phenomenon or the relationships between variables that you wish to explore. A well-defined research problem sets the stage for a focused and effective hypothesis.
Step 5: Phrase your hypothesis in three ways. To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable. If a first-year student starts attending more lectures, then their exam scores will improve.
The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a 'if-then' structure. 3.
Another example for a directional one-tailed alternative hypothesis would be that. H1: Attending private classes before important exams has a positive effect on performance. Your null hypothesis would then be that. H0: Attending private classes before important exams has no/a negative effect on performance.
Variables in a hypothesis. In any research hypothesis, variables play a critical role. These are the elements or factors that the researcher manipulates, controls, or measures. Understanding variables is essential for crafting a clear, testable hypothesis and for the stages of research that follow, such as data collection and analysis.
Research hypothesis checklist. Once you've written a possible hypothesis, make sure it checks the following boxes: It must be testable: You need a means to prove your hypothesis. If you can't test it, it's not a hypothesis. It must include a dependent and independent variable: At least one independent variable ( cause) and one dependent ...
An effective hypothesis in research is clearly and concisely written, and any terms or definitions clarified and defined. Specific language must also be used to avoid any generalities or assumptions. Use the following points as a checklist to evaluate the effectiveness of your research hypothesis: Predicts the relationship and outcome.
Based on your research question and preliminary research, now you can create your hypothesis. A good hypothesis should be clear, concise, and testable. It typically takes a statement form, predicting a potential outcome or relationship between variables. Make sure that your hypothesis is focused and answers your research question.
Step 8: Test your Hypothesis. Design an experiment or conduct observations to test your hypothesis. Example: Grow three sets of plants: one set exposed to 2 hours of sunlight daily, another exposed to 4 hours, and a third exposed to 8 hours. Measure and compare their growth after a set period.
A hypothesis is a tentative statement about the relationship between two or more variables. It is a specific, testable prediction about what you expect to happen in a study. It is a preliminary answer to your question that helps guide the research process. Consider a study designed to examine the relationship between sleep deprivation and test ...
A research hypothesis (also called a scientific hypothesis) is a statement about the expected outcome of a study (for example, a dissertation or thesis). To constitute a quality hypothesis, the statement needs to have three attributes - specificity, clarity and testability. Let's take a look at these more closely.
Once you decide on the specific problem or question you want to address, you can write your research hypothesis. Use this five-step system to hone your null hypothesis and generate your alternative hypothesis. Step 1: Create your research question. This topic should interest and excite you; answering it provides relevant information to an ...
This statement is based on background research and current knowledge.8,9 The research hypothesis makes a specific prediction about a new phenomenon10 or a formal statement on the expected relationship between an independent variable and a dependent variable.3,11 It provides a tentative answer to the research question to be tested or explored.4.
Step 3: Build the Hypothetical Relationship. In understanding how to compose a hypothesis, constructing the relationship between the variables is key. Based on your research question and variables, predict the expected outcome or connection.
A research hypothesis, in its plural form "hypotheses," is a specific, testable prediction about the anticipated results of a study, established at its outset. It is a key component of the scientific method. Hypotheses connect theory to data and guide the research process towards expanding scientific understanding.
There are 5 main steps in hypothesis testing: State your research hypothesis as a null hypothesis and alternate hypothesis (H o) and (H a or H 1 ). Collect data in a way designed to test the hypothesis. Perform an appropriate statistical test. Decide whether to reject or fail to reject your null hypothesis. Present the findings in your results ...
Learning how to write a hypothesis comes down to knowledge and strategy. So where do you start? Learn how to make your hypothesis strong step-by-step here. ... proposal or prediction. For example, a research hypothesis is formatted in an if/then statement: If a person gets less than eight hours of sleep, then they will be less motivated at work ...
Ensure that your hypothesis is realistic and can be tested within the constraints of your available resources, time, and ethical considerations. Avoid value judgments: Be neutral and objective. Avoid including personal beliefs, value judgments, or subjective opinions. Stick to empirical statements based on evidence.
Here are some tips for crafting a well-crafted hypothesis: Consider the goal of your research: Think about what it is that you want to learn or determine from your experiment and make sure that your hypothesis reflects this goal. Create an educated guess as to why something is happening: Your hypothesis should explain why something is occurring ...
A strong hypothesis makes a prediction between the relationship of the variables and outcome of the project. A variable is a factor in a scientific experiment that may be subject to change.. Good research only changes one variable at a time.This is to ensure that you can isolate and study the impact of only one variable at a time.
"My research in the Roberts group seeks to resolve regioselectivity and reactivity issues within aryne methodology via ligand control," Brylon says. "To accomplish this task, I have taken a mechanistic and hypothesis driven approach to understand how key molecular parameters modify regioselectivity and reactivity.