what is research methodology.net

What Is Research Methodology? A Plain-Language Explanation & Definition (With Examples)

By Derek Jansen (MBA)  and Kerryn Warren (PhD) | June 2020 (Last updated April 2023)

If you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!

In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.

Research Methodology 101

• What exactly research methodology means
• What qualitative , quantitative and mixed methods are
• What sampling strategy is
• What data collection methods are
• What data analysis methods are
• How to choose your research methodology
• Example of a research methodology

What is research methodology?

Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how  a researcher  systematically designs a study  to ensure valid and reliable results that address the research aims, objectives and research questions . Specifically, how the researcher went about deciding:

• What type of data to collect (e.g., qualitative or quantitative data )
• Who  to collect it from (i.e., the sampling strategy )
• How to  collect  it (i.e., the data collection method )
• How to  analyse  it (i.e., the data analysis methods )

Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just   what methodological choices were made, but also explains  why they were made. In other words, the methodology chapter should justify  the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions. 

So, it’s the same as research design?

Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here .

Need a helping hand?

What are qualitative, quantitative and mixed-methods?

Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words , numbers or both . This is a bit of an oversimplification, but its a good starting point for understanding.

Let’s take a closer look.

Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data . Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.

It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory  in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president. 

Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory  in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses .

As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.

What is sampling strategy?

Simply put, sampling is about deciding who (or where) you’re going to collect your data from . Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).

How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study.  There are many different sampling methods  you can choose from, but the two overarching categories are probability   sampling and  non-probability   sampling .

Probability sampling  involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable  to the entire population. 

Non-probability sampling , on the other hand,  doesn’t use a random sample . For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable .

To learn more about sampling methods, be sure to check out the video below.

What are data collection methods?

As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:

• Interviews (which can be unstructured, semi-structured or structured)
• Focus groups and group interviews
• Surveys (online or physical surveys)
• Observations (watching and recording activities)
• Biophysical measurements (e.g., blood pressure, heart rate, etc.)
• Documents and records (e.g., financial reports, court records, etc.)

The choice of which data collection method to use depends on your overall research aims and research questions , as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.

What are data analysis methods?

Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative  (words-based) or quantitative (numbers-based).

Popular data analysis methods in qualitative research include:

• Qualitative content analysis
• Thematic analysis
• Discourse analysis
• Narrative analysis
• Interpretative phenomenological analysis (IPA)
• Visual analysis (of photographs, videos, art, etc.)

Qualitative data analysis all begins with data coding , after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions . In the video below, we explore some  common qualitative analysis methods, along with practical examples.  

Moving on to the quantitative side of things, popular data analysis methods in this type of research include:

• Descriptive statistics (e.g. means, medians, modes )
• Inferential statistics (e.g. correlation, regression, structural equation modelling)

Again, the choice of which data collection method to use depends on your overall research aims and objectives , as well as practicalities and resource constraints. In the video below, we explain some core concepts central to quantitative analysis.

How do I choose a research methodology?

As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology . So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.

If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis). 

Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).

Designing your research and working out your methodology is a large topic, which we cover extensively on the blog . For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components. 

Example of a research methodology chapter

In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template .

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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We can’t write your methodology for you. If you’re looking for samples, you should be able to find some sample methodologies on Google. Alternatively, you can download some previous dissertations from a dissertation directory and have a look at the methodology chapters therein.

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MLA Jansen, Derek, and Kerryn Warren. “What (Exactly) Is Research Methodology?” Grad Coach, June 2021, gradcoach.com/what-is-research-methodology/.

APA Jansen, D., & Warren, K. (2021, June). What (Exactly) Is Research Methodology? Grad Coach. https://gradcoach.com/what-is-research-methodology/

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What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

• Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
• You can easily answer any questions about your research if they arise at a later stage.
• A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
• It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
• A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
• It also helps ensure that ethical guidelines are followed while conducting research.
• A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

Writing the methods section of a research paper? Let Paperpal help you achieve perfection

Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

• Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
• Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
• Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

• Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

• Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
• Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
• Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
• Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
• Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
• Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
• Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

• One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
• Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
• Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
• Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

• Sampling: The most common type is probability sampling.
• Interviews: Commonly telephonic or done in-person.
• Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
• Document review: Reviewing existing research or documents to collect evidence for supporting the research.
• Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

• Measures of frequency (count, percent, frequency)
• Measures of central tendency (mean, median, mode)
• Measures of dispersion or variation (range, variance, standard deviation)
• Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

• Correlation: To understand the relationship between two or more variables.
• Cross-tabulation: Analyze the relationship between multiple variables.
• Regression analysis: Study the impact of independent variables on the dependent variable.
• Frequency tables: To understand the frequency of data.
• Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

• Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
• Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
• Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
• Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
• Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

• Research objectives, aims, and questions —these would help structure the research design.
• Review existing literature to identify any gaps in knowledge.
• Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
• Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
• Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

• Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
• Research method —this can be quantitative, qualitative, or mixed-method.
• Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
• Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
• Sampling —this involves selecting a representative subset of the population being studied.
• Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
• Data analysis —describe the data analysis methods you will use once you’ve collected the data.
• Research limitations —mention any limitations you foresee while conducting your research.
• Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
• Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

• Research design
• Data collection procedures
• Data analysis methods
• Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

• Participants should not be subjected to harm.
• Respect for the dignity of participants should be prioritized.
• Full consent should be obtained from participants before the study.
• Participants’ privacy should be ensured.
• Confidentiality of the research data should be ensured.
• Anonymity of individuals and organizations participating in the research should be maintained.
• The aims and objectives of the research should not be exaggerated.
• Affiliations, sources of funding, and any possible conflicts of interest should be declared.
• Communication in relation to the research should be honest and transparent.
• Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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• Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
• Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
• The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
• Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
• What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
• What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
• Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
• Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
• What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
• Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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• What Is a Research Methodology? | Steps & Tips

What Is a Research Methodology? | Steps & Tips

Published on August 25, 2022 by Shona McCombes and Tegan George. Revised on November 20, 2023.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation , or research paper , the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research and your dissertation topic .

It should include:

• The type of research you conducted
• How you collected and analyzed your data
• Any tools or materials you used in the research
• How you mitigated or avoided research biases
• Why you chose these methods
• Your methodology section should generally be written in the past tense .
• Academic style guides in your field may provide detailed guidelines on what to include for different types of studies.
• Your citation style might provide guidelines for your methodology section (e.g., an APA Style methods section ).

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Table of contents

How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, other interesting articles, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

• Aim to describe the characteristics of something?
• Explore an under-researched topic?
• Establish a causal relationship?

And what type of data did you need to achieve this aim?

• Quantitative data , qualitative data , or a mix of both?
• Primary data collected yourself, or secondary data collected by someone else?
• Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

• Why is this the best way to answer your research question?
• Is this a standard methodology in your field, or does it require justification?
• Were there any ethical considerations involved in your choices?
• What are the criteria for validity and reliability in this type of research ? How did you prevent bias from affecting your data?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalizable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalized your concepts and measured your variables. Discuss your sampling method or inclusion and exclusion criteria , as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

• How did you design the questionnaire?
• What form did your questions take (e.g., multiple choice, Likert scale )?
• Were your surveys conducted in-person or virtually?
• What sampling method did you use to select participants?
• What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

• How did you design the experiment ?
• How did you recruit participants?
• How did you manipulate and measure the variables ?
• What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

• Where did you source the material?
• How was the data originally produced?
• What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on July 4–8, 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

• Information bias
• Omitted variable bias
• Regression to the mean
• Survivorship bias
• Undercoverage bias
• Sampling bias

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

• How did you find and select participants?
• How many participants took part?
• What form did the interviews take ( structured , semi-structured , or unstructured )?
• How long were the interviews?
• How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

• What group or community did you observe? How long did you spend there?
• How did you gain access to this group? What role did you play in the community?
• How long did you spend conducting the research? Where was it located?
• How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

• What type of materials did you analyze?
• How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness store’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

• The Hawthorne effect
• Observer bias
• The placebo effect
• Response bias and Nonresponse bias
• The Pygmalion effect
• Recall bias
• Social desirability bias
• Self-selection bias

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods.

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Next, you should indicate how you processed and analyzed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

• How you prepared the data before analyzing it (e.g., checking for missing data , removing outliers , transforming variables)
• Which software you used (e.g., SPSS, Stata or R)
• Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

• Content analysis : Categorizing and discussing the meaning of words, phrases and sentences
• Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
• Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

• Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviors, but they are effective for testing causal relationships between variables .
• Qualitative: Unstructured interviews usually produce results that cannot be generalized beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
• Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalizable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

• Show that you followed established practice for your type of research
• Discuss how you decided on your approach by evaluating existing research
• Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

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
• Measures of central tendency
• Chi square tests
• Confidence interval
• Quartiles & Quantiles

Methodology

• Cluster sampling
• Stratified sampling
• Thematic analysis
• Cohort study
• Peer review
• Ethnography

Research bias

• Implicit bias
• Cognitive bias
• Conformity bias
• Hawthorne effect
• Availability heuristic
• Attrition bias

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

In a scientific paper, the methodology always comes after the introduction and before the results , discussion and conclusion . The same basic structure also applies to a thesis, dissertation , or research proposal .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

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What is Research Methodology?

Research methodology refers to the overall approach or strategy used by researchers to conduct a scientific investigation or inquiry. It involves a systematic and rigorous process of collecting, analyzing, and interpreting data to answer research questions or test hypotheses.

The methodology of research involves various components, such as Research Design , Data Collection Methods , Sampling Procedures , Data Analysis Techniques , and Ethical Considerations . The choice of methodology depends on the nature of the research problem, research questions, and the available resources.

A well-designed research methodology is essential for producing reliable and valid research results. It helps researchers to avoid bias and errors in their research, to ensure that the research findings are based on sound evidence and to make sure that the research is ethical and respects the rights of participants.

What is Research Design?

Research design refers to the framework or blueprint for conducting a research study. It encompasses the overall strategy, plan, and structure of a study that guides the collection, analysis, and interpretation of data.

A well-designed research study includes a clear statement of the research problem or question, a review of relevant literature, the selection of appropriate research methods, and the determination of data collection and analysis techniques. The research design also includes decisions regarding the sample population, sampling method, and data analysis procedures.

Research design is important because it provides a structure and a systematic approach to conducting research. A well-designed research study can increase the reliability and validity of the results, improve the generalizability of the findings, and enhance the overall quality of the research.

What are the Data Collection Methods?

Data collection methods are the various ways in which researchers gather data or information for their study. Here are some of the most commonly used data collection methods:

• Surveys: Surveys are questionnaires that are administered to a sample of individuals or groups to gather information on their beliefs, attitudes, or behaviors. Surveys can be conducted through various means, such as online, telephone, or face-to-face interviews.
• Interviews: Interviews involve a one-on-one conversation between the researcher and the participant. Interviews can be structured or unstructured, and they may be conducted in person or via phone or video conferencing.
• Focus groups: Focus groups are group interviews conducted with a small group of people who share similar characteristics or experiences. The researcher leads a discussion on a specific topic, and participants share their opinions, attitudes, and experiences.
• Observations: Observations involve the systematic recording of behaviors or events. This method can be done by a researcher directly observing the participants or by using audio or video recordings.
• Experiments: Experiments involve manipulating one or more variables to see how they affect the outcome of the study. This method is often used in scientific research and involves a control group and an experimental group.
• Case studies: Case studies involve the in-depth study of an individual, group, or event. Researchers gather data from a variety of sources, such as interviews, observations, and documents.
• Secondary data analysis: Secondary data analysis involves the use of existing data sources, such as government records, company records, or previously published research. The researcher analyzes the data to answer their research questions.

Each method has its own advantages and limitations and should be chosen based on the research questions, available resources, and ethical considerations.

What are the Sampling Procedures used in Research?

In research, sampling refers to the process of selecting a subset of individuals or units from a larger population for the purpose of conducting research. There are several sampling procedures used in research, including:

• Simple random sampling: In this procedure, every member of the population has an equal chance of being selected. This is done using a random number generator or a table of random numbers.
• Stratified random sampling: This involves dividing the population into subgroups (or strata) and then selecting a sample from each stratum. This is done to ensure that the sample is representative of the population as a whole.
• Cluster sampling: This involves dividing the population into clusters (such as geographic regions) and then selecting a random sample of clusters. Then, all members of the selected clusters are included in the sample.
• Systematic sampling: This involves selecting every nth individual from a list of the population. For example, if you wanted a sample of 100 individuals from a population of 1000, you would select every 10th person from the list.
• Convenience sampling: This involves selecting individuals who are easily accessible or available. This method is often used in situations where it is difficult or impractical to obtain a random sample.
• Purposive sampling: This involves selecting individuals who meet specific criteria or characteristics that are relevant to the research question. This method is often used in qualitative research.
• Snowball sampling: This involves selecting individuals who are known to the researcher or who are referred by other participants. This method is often used in situations where the population is difficult to access or locate.

It's important to note that each sampling method has its own strengths and weaknesses and that the method used will depend on the research question and the characteristics of the population being studied.

What are the Data Analysis Techniques used in Research?

There are many data analysis techniques used in research, and the choice of technique depends on the type of data collected, the research questions, and the hypotheses being tested. Some of the commonly used data analysis techniques are:

• Descriptive statistics: Descriptive statistics include measures of central tendency (mean, median, mode) and measures of variability (standard deviation, range, interquartile range) that are used to summarize and describe the data.
• Inferential statistics: Inferential statistics involve making inferences or drawing conclusions about a population based on a sample of data. Techniques include hypothesis testing, confidence intervals, and regression analysis.
• Qualitative data analysis: Qualitative data analysis involves analyzing data that is non-numeric in nature, such as text or images. Techniques include content analysis, grounded theory, and thematic analysis.
• Data mining: Data mining involves using computational algorithms to analyze large datasets and identify patterns or relationships that may not be immediately apparent. Techniques include association rule mining, clustering, and classification.
• Network analysis: Network analysis involves analyzing the relationships between nodes in a network, such as social networks or communication networks. Techniques include centrality analysis, community detection, and network visualization.
• Machine learning: Machine learning involves using algorithms to automatically learn patterns in data and make predictions or classifications. Techniques include decision trees, neural networks, and support vector machines.
• Text analytics: Text analytics involves analyzing large volumes of text data to identify patterns or relationships. Techniques include sentiment analysis, topic modeling, and named entity recognition.
• Time series analysis: Time series analysis involves analyzing data that is collected over time, such as stock prices or weather data. Techniques include autoregressive integrated moving average (ARIMA) models, exponential smoothing, and spectral analysis.

The choice of data analysis technique(s) depends on the research question(s), the type of data collected, and the goals of the research study.

What Ethical Considerations Should be Taken Care of While Performing a Research?

Performing research entails a significant amount of responsibility, including ethical considerations that should be taken into account throughout the entire research process. The following are some of the key ethical considerations that should be taken care of while performing research:

• Informed Consent: Researchers should obtain informed consent from study participants before conducting any research on them. This includes providing participants with detailed information about the study, including the purpose, procedures, risks, and benefits. Participants must have the right to decline to participate or withdraw from the study at any time.
• Confidentiality: Researchers should protect the confidentiality and privacy of study participants by ensuring that their personal information is kept secure and that their identities are kept anonymous or pseudonymous. Researchers should also inform participants of the limitations of confidentiality, such as legal requirements to report certain findings.
• Avoiding Harm: Researchers must take measures to prevent harm to study participants, including both physical and psychological harm. This may include providing counseling or support services for participants who may experience distress as a result of the research.
• Fairness: Researchers should treat all participants fairly and ensure that they are not discriminated against based on their race, ethnicity, gender, age, religion, or other factors.
• Integrity: Researchers must maintain high standards of research integrity, including being honest and transparent about their methods and findings, avoiding conflicts of interest, and adhering to ethical codes and guidelines.
• Respect: Researchers must respect the autonomy, dignity, and rights of study participants, as well as other stakeholders, such as research sponsors, regulators, and the wider community.
• Responsible Conduct: Researchers should conduct research with a sense of responsibility towards society and the environment. They should consider the potential impact of their research on the community and the environment, and ensure that their research is conducted in a socially responsible and sustainable manner.

In summary, ethical considerations should be an integral part of the research process from its inception through dissemination. By adhering to these ethical principles, researchers can promote the integrity and credibility of their research, protect the welfare of study participants, and contribute to the advancement of knowledge in a responsible and respectful manner.

Managing Editor , International Journal of Science and Research (IJSR)

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What is research methodology?

The basics of research methodology

Why do you need a research methodology, what needs to be included, why do you need to document your research method, what are the different types of research instruments, qualitative / quantitative / mixed research methodologies, how do you choose the best research methodology for you, frequently asked questions about research methodology, related articles.

When you’re working on your first piece of academic research, there are many different things to focus on, and it can be overwhelming to stay on top of everything. This is especially true of budding or inexperienced researchers.

If you’ve never put together a research proposal before or find yourself in a position where you need to explain your research methodology decisions, there are a few things you need to be aware of.

Once you understand the ins and outs, handling academic research in the future will be less intimidating. We break down the basics below:

A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more.

You can think of your research methodology as being a formula. One part will be how you plan on putting your research into practice, and another will be why you feel this is the best way to approach it. Your research methodology is ultimately a methodological and systematic plan to resolve your research problem.

In short, you are explaining how you will take your idea and turn it into a study, which in turn will produce valid and reliable results that are in accordance with the aims and objectives of your research. This is true whether your paper plans to make use of qualitative methods or quantitative methods.

The purpose of a research methodology is to explain the reasoning behind your approach to your research - you'll need to support your collection methods, methods of analysis, and other key points of your work.

Think of it like writing a plan or an outline for you what you intend to do.

When carrying out research, it can be easy to go off-track or depart from your standard methodology.

Tip: Having a methodology keeps you accountable and on track with your original aims and objectives, and gives you a suitable and sound plan to keep your project manageable, smooth, and effective.

With all that said, how do you write out your standard approach to a research methodology?

As a general plan, your methodology should include the following information:

• Your research method.  You need to state whether you plan to use quantitative analysis, qualitative analysis, or mixed-method research methods. This will often be determined by what you hope to achieve with your research.
• Explain your reasoning. Why are you taking this methodological approach? Why is this particular methodology the best way to answer your research problem and achieve your objectives?
• Explain your instruments.  This will mainly be about your collection methods. There are varying instruments to use such as interviews, physical surveys, questionnaires, for example. Your methodology will need to detail your reasoning in choosing a particular instrument for your research.
• What will you do with your results?  How are you going to analyze the data once you have gathered it?
• Advise your reader.  If there is anything in your research methodology that your reader might be unfamiliar with, you should explain it in more detail. For example, you should give any background information to your methods that might be relevant or provide your reasoning if you are conducting your research in a non-standard way.
• How will your sampling process go?  What will your sampling procedure be and why? For example, if you will collect data by carrying out semi-structured or unstructured interviews, how will you choose your interviewees and how will you conduct the interviews themselves?
• Any practical limitations?  You should discuss any limitations you foresee being an issue when you’re carrying out your research.

In any dissertation, thesis, or academic journal, you will always find a chapter dedicated to explaining the research methodology of the person who carried out the study, also referred to as the methodology section of the work.

A good research methodology will explain what you are going to do and why, while a poor methodology will lead to a messy or disorganized approach.

You should also be able to justify in this section your reasoning for why you intend to carry out your research in a particular way, especially if it might be a particularly unique method.

Having a sound methodology in place can also help you with the following:

• When another researcher at a later date wishes to try and replicate your research, they will need your explanations and guidelines.
• In the event that you receive any criticism or questioning on the research you carried out at a later point, you will be able to refer back to it and succinctly explain the how and why of your approach.
• It provides you with a plan to follow throughout your research. When you are drafting your methodology approach, you need to be sure that the method you are using is the right one for your goal. This will help you with both explaining and understanding your method.
• It affords you the opportunity to document from the outset what you intend to achieve with your research, from start to finish.

A research instrument is a tool you will use to help you collect, measure and analyze the data you use as part of your research.

The choice of research instrument will usually be yours to make as the researcher and will be whichever best suits your methodology.

There are many different research instruments you can use in collecting data for your research.

Generally, they can be grouped as follows:

• Interviews (either as a group or one-on-one). You can carry out interviews in many different ways. For example, your interview can be structured, semi-structured, or unstructured. The difference between them is how formal the set of questions is that is asked of the interviewee. In a group interview, you may choose to ask the interviewees to give you their opinions or perceptions on certain topics.
• Surveys (online or in-person). In survey research, you are posing questions in which you ask for a response from the person taking the survey. You may wish to have either free-answer questions such as essay-style questions, or you may wish to use closed questions such as multiple choice. You may even wish to make the survey a mixture of both.
• Focus Groups.  Similar to the group interview above, you may wish to ask a focus group to discuss a particular topic or opinion while you make a note of the answers given.
• Observations.  This is a good research instrument to use if you are looking into human behaviors. Different ways of researching this include studying the spontaneous behavior of participants in their everyday life, or something more structured. A structured observation is research conducted at a set time and place where researchers observe behavior as planned and agreed upon with participants.

These are the most common ways of carrying out research, but it is really dependent on your needs as a researcher and what approach you think is best to take.

It is also possible to combine a number of research instruments if this is necessary and appropriate in answering your research problem.

There are three different types of methodologies, and they are distinguished by whether they focus on words, numbers, or both.

➡️ Want to learn more about the differences between qualitative and quantitative research, and how to use both methods? Check out our guide for that!

If you've done your due diligence, you'll have an idea of which methodology approach is best suited to your research.

It’s likely that you will have carried out considerable reading and homework before you reach this point and you may have taken inspiration from other similar studies that have yielded good results.

Still, it is important to consider different options before setting your research in stone. Exploring different options available will help you to explain why the choice you ultimately make is preferable to other methods.

If proving your research problem requires you to gather large volumes of numerical data to test hypotheses, a quantitative research method is likely to provide you with the most usable results.

If instead you’re looking to try and learn more about people, and their perception of events, your methodology is more exploratory in nature and would therefore probably be better served using a qualitative research methodology.

It helps to always bring things back to the question: what do I want to achieve with my research?

Once you have conducted your research, you need to analyze it. Here are some helpful guides for qualitative data analysis:

➡️  How to do a content analysis

➡️  How to do a thematic analysis

➡️  How to do a rhetorical analysis

Research methodology refers to the techniques used to find and analyze information for a study, ensuring that the results are valid, reliable and that they address the research objective.

Data can typically be organized into four different categories or methods: observational, experimental, simulation, and derived.

Writing a methodology section is a process of introducing your methods and instruments, discussing your analysis, providing more background information, addressing your research limitations, and more.

Your research methodology section will need a clear research question and proposed research approach. You'll need to add a background, introduce your research question, write your methodology and add the works you cited during your data collecting phase.

The research methodology section of your study will indicate how valid your findings are and how well-informed your paper is. It also assists future researchers planning to use the same methodology, who want to cite your study or replicate it.

Method vs Methodology: What are the Key Differences?

Explore the key differences between method and methodology in research. Learn how to effectively apply these concepts for rigorous and impactful results.

Kate Windsor

Jun 23, 2024

Introduction 

Have you ever found yourself confused about the terms "method" and "methodology" while conducting research or writing a scientific paper ? You're not alone. Many researchers, students, and professionals often use these terms (methodology and method) interchangeably, but they actually have distinct meanings and implications. 

In this article, we'll explore the key differences between method vs methodology, and why understanding this distinction is crucial for effective research and writing, especially when trying to answer your research question.

What is a Method?

A method including research method refers to a specific procedure, technique, or tool used to collect, analyze, or interpret data within a research study. It is a concrete, well-defined set of steps that researchers use to gather and process information to support or reject the research hypothesis.

Methods are often specific to a particular discipline or field of study, and they can be either quantitative methods (involving numerical data and statistical analysis) or qualitative methods (involving non-numerical data, such as observations or interviews).

Examples of methods include surveys, experiments, case studies, and statistical analysis techniques, such as regression or factor analysis. These are all examples of when to use specific methods to collect your data and conduct your research. For more information on different types of research, check out our article on theoretical vs. applied research .

What is a Methodology?

In contrast to a method, a methodology refers to the overarching approach to both quantitative research and qualitative research. It encompasses the overall strategy, design, and philosophical assumptions that guide the selection and application of specific methods.

A methodology provides a framework for understanding the research topic, formulating research questions, and interpreting the findings. It considers factors such as the researcher's theoretical perspective, the nature of the research problem, and the intended audience for the research. 

Examples of methodologies include grounded theory, ethnography, phenomenology, and action research. These methodologies serve as a justification for using a particular set of methods to conduct your research and answer your research question. If you're a PhD student looking to strengthen your research skills, our writing tips for PhD students may be helpful.

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Key Differences between Method and Methodology

• Scope and focus: A method focuses on the specific tools and techniques used to collect and analyze data, while a methodology encompasses the broader approach to a particular research, including the philosophical assumptions and theoretical perspectives that guide choice of methods.
• Level of abstraction: Methods are concrete and specific, providing a step-by-step guide for data collection and analysis methods. Methodologies, on the other hand, are more abstract and conceptual, dealing with the overarching principles and strategies that inform the research process.
• Role in the research process: Methods are applied during the data collection and analysis stages of research, while methodologies shape the entire research process, from the formulation of the research question to the interpretation of the findings. Understanding this difference is essential when writing a research proposal or a research paper in your research approach.
• Flexibility and adaptability: While methods are often fixed and standardized, methodologies can be more flexible and adaptable to the specific needs and contexts of a research study. Researchers may combine or modify methodologies to better suit their research aims or objectives and the nature of the problem being investigated.

The Importance of Understanding the Difference Understanding the difference between method and methodology is crucial for several reasons:

• Clarity in research design and communication: Clearly distinguishing between methods and methodologies helps researchers design more coherent and rigorous studies. It also enables them to communicate their research effectively to others, including peers, funding agencies, and the wider public. If you struggle with writing efficiently, our article on how to write faster may offer some useful strategies.
• Proper selection and application of methods and methodologies: By understanding the distinction between methods and methodologies, researchers can more effectively select and apply the appropriate tools and approaches for their specific research goals. This helps ensure that the research is valid, reliable, and relevant to the problem being investigated.
• Implications for the quality and reliability of research findings: Confusing methods and methodologies can lead to inconsistencies, errors, or limitations in the research process, which can ultimately affect the quality and reliability of the findings. By properly understanding and applying these concepts, researchers can produce more robust and trustworthy results. The use of AI in research is also becoming increasingly important for enhancing the accuracy and efficiency of data analysis.

Real-World Examples

Let's consider a couple of examples to illustrate the difference between method and methodology in practice:

**Example 1:  **A researcher wants to investigate the impact of social media on adolescent mental health. The researcher's methodology may be a mixed-methods approach, combining quantitative surveys with qualitative interviews to gain a comprehensive understanding of the issue.

The specific methods used could include an online questionnaire to collect data or any type of data on social media usage and mental health outcomes, as well as semi-structured interviews with a subset of participants to explore their experiences in-depth.

**Example 2: **A researcher plans to study the effectiveness of a new teaching strategy in primary schools. The research methodologies may be a quasi-experimental design, comparing the performance of students in classrooms using the new strategy with those using traditional methods.

The specific methods used could include pre- and post-tests to measure student learning outcomes, classroom observations to assess teacher implementation of the strategy, and focus groups with teachers and students to gather qualitative feedback.

In both examples, the methodology provides the overarching framework and approach for the research, while the methods are the specific tools and techniques used to collect and analyze data within that framework.

Confusing or conflating these concepts could lead to a misalignment between the research objectives and the actual data collected, potentially undermining the validity and impact of the findings.

Methods research is a crucial aspect of conducting effective and reliable studies. By carefully selecting and applying the appropriate methods, researchers can gather the necessary data and methods to support or reject their hypotheses and contribute to the broader body of knowledge in their field. Whether conducting medical research, social science research, or any other type of inquiry, a well-designed research strategy that incorporates suitable methods is essential for achieving meaningful results.

In summary, while methods and methodologies are closely related, they serve distinct purposes in the research process. Methods are the specific tools and techniques used to collect and analyze data, while methodologies are the broader approaches that guide the selection and application of those methods.

Understanding this distinction is essential for designing rigorous and effective research studies, communicating research findings clearly, and ensuring the reliability and impact of the results. As you embark on your own research journey, whether you're writing a PhD proposal or conducting a study, keep this important distinction in mind to strengthen your research skills and outcomes.

Q: What is the purpose of the methods section in a section of a research paper? A: The methods section in a research paper describes the specific procedures, techniques, and tools used to collect and analyze data in a study. It provides a detailed account of how the research was conducted, allowing other researchers to understand, evaluate, and potentially replicate the study.

**Q: Is the study of methods the same as methodology? **A: No, the study of methods focuses on the specific tools and techniques used in research, while methodology refers to the broader philosophical and strategic approach that guides the selection and application of those methods.

Q: What is the difference between the methodology section and the method and methodology section in a research paper? A: The methodology section discusses the overall approach to the research, including the philosophical assumptions, research design, and rationale for the chosen methods. The method and methodology section, on the other hand, combines the description of the specific methods used with the broader methodological framework.

Q: Can several methods be used in research? A: Yes, researchers often apply several methods in a single study to gather and analyze data from different perspectives. This approach, known as triangulation, can help increase the validity and reliability of the findings.

Q: How are methods and methodologies used in research? A: Methods are the specific tools and techniques used in research to collect and analyze data, such as surveys, experiments, interviews, or statistical tests. Methodologies, in contrast, provide the overarching framework and approach that guide the selection and application of these methods based on the research objectives, philosophical assumptions, and the nature of the problem being investigated.

**Q: Can methods and methodologies be applied to UX research? **A: Yes, UX research relies on various methods and methodologies to gather insights into user behavior, preferences, and experiences. For example, user interviews, usability testing, and surveys are common methods used in UX research, while user-centered design and lean UX are examples of methodologies that guide the overall approach to UX research and design.

Q: What methods and methodologies are used in experimental research? A: Experimental research typically involves methods such as randomized controlled trials, A/B testing, and factorial designs to manipulate variables and measure their effects on outcomes. The methodology guiding experimental research is often rooted in the scientific method, which emphasizes hypothesis testing, control groups, and the systematic manipulation of variables to establish cause-and-effect relationships. These methods are crucial for conducting rigorous analysis of the research methods and ensuring the validity of the findings.

Understanding the difference between method and methodology is crucial for conducting effective research. While methodology refers to the overarching approach and strategy guiding the research process, methods are the tools and techniques used to collect and analyze data. When deciding on using a particular research method, it's essential to consider the nature of your research question and the type of data you want to measure.

Whether you employ quantitative and qualitative methods or a combination of both, the ultimate goal is to select the most appropriate methods to answer your research question effectively. Remember, research deals with complex issues, and no single method is simply a one-size-fits-all solution.

By carefully evaluating your research objectives and the resources available, you can determine which method or alternative method might be best suited for your study. With a well-designed methodology and carefully chosen methods, you can contribute valuable insights to your field and advance our understanding of the world around us. 

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The Average American Family's $1,063,700 Net Worth Could Be Yours if You Do These Things

Published on June 27, 2024

By: Maurie Backman

• Automating your savings can set you on a solid path.
• Investing in stocks can result in strong returns.
• Owning a home could increase your net worth -- but don't stress if that's not in the cards.

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As someone who likes to be on top of her finances, I have a pretty good idea of how much money is in my checking account at any given point. Similarly, I'm aware of how much emergency savings I have, and I know what my credit card balances look like.

In case you're not familiar with the term or aren't quite sure what it means, your net worth is the sum of your assets minus your liabilities, or debts. As a basic example, let's say you own a home worth $500,000 and have $50,000 in your savings account . That means you've got $550,000 in assets. If your only debt is a mortgage you owe $400,000 on, your net worth is $150,000.

Recent data from the Federal Reserve puts the average American family's net worth at $1,063,700. Of course, it's worth keeping in mind that a small percentage of very high net worth families could be pulling the average up.

The median net worth among American families is just $192,900. And that discrepancy tells us that $192,000 is more indicative of the typical family's net worth than $1,063,700.

But a net worth of $1 million and change may actually be more attainable than you'd think. Here's how to get to a number like that.

1. Get into the habit of saving money automatically

Growing your net worth starts with solid financial habits. Spending less than you earn is a core one. Some people make the mistake of collecting their paychecks, paying their bills, seeing what's left at the end of the month, and then putting money into savings.

A better bet is to automate the savings process so you're setting money aside for different goals off the bat -- before you've gotten a chance to spend your paycheck in full. You can automate your savings in different ways, but a few popular options include:

• Setting up an automatic transfer from a checking account to a savings account
• Signing up for an employer's 401(k)
• Arranging for money to go from a checking account to an IRA

2. Invest your money in the stock market

Here's a little secret -- you don't have to save $1 million and change to end up with that sum of money. If you invest over a long period of time, you can potentially turn a small sum of money into a much larger one.

The stock market's average annual return over the past 50 years has been 10%, accounting for good years and bad. So let's say you get into the habit of saving $500 a month, whether for retirement or another goal, and you do so over 31 years. If you invest your savings in stocks and your portfolio delivers that same 10% return, you could end up with $1.09 million and change -- a bit more than the average family net worth today.

3. Buy a home -- or invest the money you're not spending on homeownership

Home values have a tendency to rise over time. So buying a home is a great way to grow your net worth. If you purchase a home for $300,000 and its value increases to $750,000 over 30 years, you've just gained $450,000 in net worth.

However, don't stress if homeownership seems unattainable for you, or if it's just not something you're interested in. Owning a home costs a lot of money beyond your down payment and mortgage. There's upkeep, repairs, and property tax bills, just to name a few expenses. Owning a home also requires a lot of actual work on your part -- work you may not want to do.

There's no reason to write off the idea of growing your net worth to $1 million or more just because you don't own a home. If you take the money you aren't spending on homeownership expenses and invest it instead, you could come out way ahead financially.

Don't obsess over your net worth -- but set yourself up to grow it

The reason I don't fixate on my net worth is that it doesn't necessarily impact my day-to-day spending. For example, I have a lot of my net worth tied up in my home. But since I'm not selling it, that's not money I can use to pay bills right now.

For this reason, I'd encourage you to focus more on covering your incoming expenses and fixate less on your net worth. But now that you know how to grow yours, you can set yourself up to be worth a lot of money one day down the line.

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Our Research Expert

Maurie Backman is a personal finance writer covering topics ranging from Social Security to credit cards to mortgages. She also has an editing background and has hosted personal finance podcasts.

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UGC NET Syllabus 2024: Download Paper 1 & Paper 2 Syllabus PDF

Ugc net syllabus 2024 for paper 1 and 2 has been released by the university grants commission. prospective candidates should review the subject-wise ugc net syllabus and exam pattern in both hindi and english before commencing their preparation. additionally, you can find the direct link to download the ugc net syllabus 2024 pdf here..

UGC NET Syllabus 2024 is prescribed by the University Grants Commission along with the notification. Aspirants planning to appear for the UGC NET exam, scheduled to be held on June 18,  must be conversant with the detailed syllabus. The exam is divided into two papers: Paper 1 and Paper 2. While Paper 1 is compulsory for all candidates, Paper 2 depends on the subject chosen by the candidates. There are a total of 83 UGC NET subjects from which the candidates have to choose.

UGC NET Syllabus 2024

The UGC NET exam is held twice a year to ascertain candidates' eligibility for Assistant Professor positions or both Junior Research Fellowship (JRF) and Assistant Professor roles in Indian universities and colleges. Lakhs of candidates appear for the exam; however, only a few are able to crack it. For the December 2023 session, 9.45 lakh candidates registered for the exam, but only 6.55 lakh candidates appeared for it.

UGC NET Syllabus 2024 for Paper 1

UGC NET Paper 1 Syllabus 2024 Subject-wise

Unit-i: teaching aptitude syllabus.

• Teaching: Concept, Objectives, Levels of teaching (Memory, Understanding and Reflection), Characteristics and basic requirements.
• Learner’s characteristics: Characteristics of adolescent and adult learners (Academic, Social, Emotional and Cognitive), Individual differences.
• Factors affecting teaching related to Teacher, Learner, Support material, Instructional facilities, Learning environment and Institution.
• Methods of teaching in Institutions of higher learning: Teacher centred vs. Learner-centred methods; offline vs. Online methods (Swayam, Swayamprabha, MOOCs etc.).
• Teaching Support System: Traditional, Modern and ICT based.
• Evaluation Systems: Elements and Types of evaluation, Evaluation in Choice Based Credit System in Higher education, Computer-based testing, Innovations in evaluation systems.

Unit-II: Research Aptitude Syllabus

• Research: Meaning, Types, and Characteristics, Positivism and Postpositivistic approach to research.
• Methods of Research: ExperimeUGCl, Descriptive, Historical, Qualitative and Quantitative Methods, Steps of Research.
• Thesis and Article writing: Format and styles of referencing.
• Application of ICT in research.
• Research ethics.

Unit-III Comprehension Syllabus

Unit-iv: communication.

• Communication: Meaning, types and characteristics of communication.
• Effective communication: Verbal and Non-verbal, Inter-Cultural and group communications, Classroom communication.
• Barriers to effective communication.
• Mass-Media and Society.

Unit-V: Mathematical Reasoning and Aptitude Syllabus

• Types of reasoning.
• Number series, Letter series, Codes and Relationships.
• Mathematical Aptitude (Fraction, Time & Distance, Ratio, Proportion and PerceUGCge, Profit and Loss, Interest and Discounting, Averages etc.).

Unit-VI: Logical Reasoning Syllabus

• Understanding the structure of arguments: argument forms, the structure of categorical propositions, Mood and Figure, Formal and Informal fallacies, Uses of language, Connotations and denotations of terms, Classical square of opposition.
• Evaluating and distinguishing deductive and inductive reasoning.
• Venn diagram: Simple and multiple uses for establishing the validity of arguments.
• Indian Logic: Means of knowledge.
• Pramanas: Pratyaksha (Perception), Anumana (Inference), Upamana (Comparison), Shabda (Verbal testimony), Arthapatti (Implication) and Anupalabddhi (Non-apprehension).
• Structure and kinds of Anumana (inference), Vyapti (invariable relation), Hetvabhasas (fallacies of inference).

UGC NET Exam Pattern

• UGC NET Eligibility
• UGC NET Preparation

Unit-VII: Data Interpretation Syllabus

• Sources, acquisition and classification of Data.
• Quantitative and Qualitative Data.
• Graphical representation (Bar-chart, Histograms, Pie-chart, Table-chart and Line-chart) and mapping of Data.
• Data Interpretation.
• Data and Governance.
• Unit-VIII: Information and Communication Technology (ICT) Syllabus
• ICT: General abbreviations and terminology.
• Basics of the Internet, Intranet, E-mail, Audio and Video-conferencing.
• Digital initiatives in higher education.
• ICT and Governance.

Unit-IX: People, Development and Environment Syllabus

• Development and environment: Millennium development and Sustainable development goals.
• Human and environment interaction: Anthropogenic activities and their impacts on the environment.
• EnvironmeUGCl issues: Local, Regional and Global; Air pollution, Water pollution, Soil pollution, Noise pollution, Waste (solid, liquid, biomedical, hazardous, electronic), Climate change and its Socio-Economic and Political dimensions.
• Impacts of pollutants on human health.
• Natural and energy resources: Solar, Wind, Soil, Hydro, Geothermal, Biomass, Nuclear and Forests.
• Natural hazards and disasters: Mitigation strategies.
• EnvironmeUGCl Protection Act (1986), National Action Plan on Climate Change, International agreements/efforts -Montreal Protocol, Rio Summit, Convention on Biodiversity, Kyoto Protocol, Paris Agreement, International Solar Alliance.

Unit-X: Higher Education System Syllabus

• Institutions of higher learning and education in ancient India.
• Evolution of higher learning and research in Post Independence India.
• OrieUGCl, Conventional and Non-conventional learning programmes in India.
• Professional, Technical and Skill-Based education.
• Value education and environmeUGCl education.
• Policies, Governance, and Administration.

UGC NET Syllabus PDF Paper 1

Individuals preparing for exam can access the UGC NET Paper 1 syllabus PDF either on the official website or click on the direct link mentioned below. Downloading UGC NET Syllabus Paper 1 PDF 2024 will be highly beneficial while preparing for the exam. 

⇒   UGC NET Paper 1 Syllabus PDF in English

UGC NET Paper 2 Syllabus PDF

UGC NET Paper 2 includes 83 subjects. Candidates should choose the subject in which they have completed their master's degree. If their chosen subject is not listed, they should select a related subject. The UGC NET Syllabus PDF for Paper 2 is mentioned in the article below for your convenience.

UGC NET Paper 2 Syllabus 2024 Subject-wise

UGC NET Syllabus Political Science

Candidates who have completed their master's in Political Science and selected this subject for UGC NET Paper 2 must possess a comprehensive understanding of the syllabus.

• Political Traditions
• Conservatism
• Multiculturalism
• Postmodernism
• Confucius, Plato, Aristotle, Machiavelli, Hobbes, Locke, Rousseau, Hegel, Mary Wollstonecraft, John Stuart Mill, Karl Marx, Gramsci, Hannah Arendt, Frantz
• Fanon, Mao Zedong, John Rawls

UGC NET Syllabus Law

Candidates gearing up for the UGC NET Law examination should thoroughly review the syllabus to devise an effective study plan. The subject code for UGC NET Law is 58, encompassing a syllabus consisting of 10 units. Check out the UGC NET Law Syllabus below.

• Nature and sources of law
• Schools of jurisprudence
• Law and morality
• Concept of rights and duties
• Legal personality
• Concepts of property, ownership, and possession
• Concept of liability
• Law, poverty, and development
• Global justice
• Modernism and post-modernism
• Preamble, fundameUGCl rights and duties, directive principles of state
• Union and State executive and their interrelationship
• Union and State legislature and distribution of legislative powers
• Emergency provisions
• Temporary, transitional and special provisions in respect of certain states
• Election Commission of India
• Nature, scope and importance of administrative law
• Principle of natural justice
• Judicial review of administrative actions 
• International law – Definition, nature and basis
• Sources of International law
• Recognition of states and governments
• Nationality, immigrants, refugees and internally displaced persons (IDPs)
• Extradition and asylum
• United Nations and its organs
• Settlement of international disputes
• World Trade Organization (WTO)
• International humanitarian law (IHL) - Conventions and protocols
• ImplemeUGCtion of IHL - Challenges
• General principles of criminal liability – Actus reus and mens rea, individual and group liability and constructive liability
• Stages of crime and inchoate crimes - Abetment, criminal conspiracy and attempt
• General exceptions
• Offences against human body
• Offences against state and terrorism
• Offences against property
• Offences against women and children
• Drug trafficking and counterfeiting
• Offences against public tranquility
• Theories and kinds of punishments, compensation to the victims of crime
• Nature and definition of tort
• General principles of tortious liability
• General defenses
• Specific torts – Negligence, nuisance, trespass and defamation
• Remoteness of damages
• Strict and absolute liability
• Tortious liability of the State
• The Consumer Protection Act 1986 - Definitions, consumer rights and redressal mechanism
• The Motor Vehicles Act, 1988 - No fault liability, third party insurance and claims tribunal
• The Competition Act, 2002 - Prohibition of certain agreements, abuse of dominant position and regulation of combinations
• Essential elements of contract and e-contract
• Breach of contract, frustration of contract, void and voidable agreements
• Standard form of contract and quasi-contract
• Specific contracts - Bailment, pledge, indemnity, guarantee and agency
• Sale of Goods Act, 1930
• Partnership and limited liability partnership
• Negotiable Instruments Act, 1881
• Company law – Incorporation of a company, prospectus, shares and debentures
• Company law – Directors and meetings
• Corporate social responsibility
• Sources and schools
• Marriage and dissolution of marriage
• Matrimonial remedies - Divorce and theories of divorce
• Changing dimensions of institution of marriage – Live-in relationship
• Recognition of foreign decrees in India on marriage and divorce
• Maintenance, dower and stridhan
• Adoption, guardianship and acknowledgement
• Succession and inheritance
• Will, gift and wakf
• Uniform Civil Code
• Meaning and concept of ‘environment’ and ‘environmeUGCl pollution’
• International environmeUGCl law and UN Conferences
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Advanced genetic tools help researchers id new neurodevelopmental syndrome.

(© stock.adobe.com)

In a recent study, a Yale-led research team described for the first time a rare neurodevelopmental syndrome that begins affecting patients during infancy, and typically causes developmental delays, severe seizures, cardiac dysrhythmia, and recurring infection.

After conducting a genetic analysis on 18 individuals with similar symptoms — but for whom there was no established diagnosis — and comparing the results with other findings, the research team, led by Yale’s Saquib Lakhani and Lauren Jeffries , was able to discern the genetic roots of what they determined was a syndrome shared by all of the patients.

According to their findings, published in the journal Genetics in Medicine, the newly defined syndrome — now known as Jeffries-Lakhani Neurodevelopment Syndrome, or JELANS — arises when patients have variants in a gene called CRELD1 , which has known roles in the cardiac and immune systems but had never before been characterized in patients with neurodevelopmental symptoms.

The discovery would not have been possible, researchers say, without next-generation DNA sequencing, a tool refined within the past decade that can rapidly sequence thousands of genes or even entire genomes.

“ The advancements in DNA sequencing have completely transformed how we approach patients,” said Lakhani , clinical director of Yale School of Medicine’s Pediatric Genomics Discovery Program and senior author of the study.

With next-generation sequencing, researchers can uncover alterations in genes — also known as variants — shared by people around the world with similar symptoms. That allows them to draw connections that may have been missed when relying on symptoms alone.

In this case, and in a growing number of others, it means a disorder that had gone undiscovered is now named and defined, giving those affected by it much-needed answers and researchers a clearer route to treatment development.

Lakhani and Jeffries, an associate research scientist and medical geneticist with the Pediatric Genomics Discovery Program and lead author of the study, recently sat down with Yale News to discuss JELANS and the process of identifying a new syndrome, how the program’s “gene-centric” approach to care yielded this discovery, and how it benefits families facing these rare disorders.

This interview has been edited and condensed.

This study included numerous individuals experiencing similar symptoms. Why did you suspect that this group of symptoms might in fact be a previously unknown syndrome?

Lauren Jeffries:  It may be surprising to know that, even in 2024, while over 7,000 rare genetic disorders are already defined, the majority of our 20,000 genes are still not well understood. So, while comparing clinical notes across patients is still critical to our work, in the   Pediatric Genomics Discovery Program  we utilize a “gene-centric” approach, meaning that instead of comparing symptoms, we look for genetic differences as our first step.

In this particular case, GeneDx — a commercial lab headquartered in Connecticut that we collaborate with — had genetically screened 10 patients who had compound heterozygous variants for the  CRELD1  gene. That means that the patients had two variants in this gene, one coming from their mom and one from their dad. GeneDx then asked if we wanted to look into this further. Most of the patients in our full cohort ended up sharing the exact same change, which was remarkably suspicious.

What is needed to identify a novel syndrome?

Saquib Lakhani: In general, you need a certain number of patients and consistency in the characteristics of those patients. You also typically need basic science evidence — which could be biochemical, cell system, or animal model testing — that corroborates that the variation in the gene in question is associated with the condition in the patients you’ve identified, and that it causes some changes or abnormalities in the scientific testing. And ultimately you need to be able to get a paper describing the syndrome published, indicating that your peers have accepted the evidence defining the syndrome.

How were you able to determine the characteristics of JELANS?

Jeffries: We worked with an incredible team of researchers to find 18 patients from 14 families in the U.S., Canada, and the U.K., including one who we cared for in our pediatric ICU here at Yale. When no established diagnoses were identified for them, their genetic data was analyzed under the research lens. From this deeper analysis of genetic data, the CRELD1 gene emerged as the candidate to study.

We also looked through their clinical data to see what patterns might exist. All of the patients had low muscle tone at birth. In the majority of cases, epilepsy developed by around five months of age, and all patients had seizures at some point in time. Cardiac dysrhythmias and recurrent infections were also common, and we noticed that several patients had shared facial features such as large-appearing eyes.

Lakhani: We then studied the gene in frogs. We first wanted to see what happened when we removed the gene, because that can give us a clue as to what the gene is important for. When we fully knocked out the gene, the frog embryos did not survive. But when the gene was partially knocked out, we found that there were a lot of developmental defects in these frogs. Interestingly, surviving tadpoles with the gene significantly knocked out were more susceptible to developing seizures. That showed us that CRELD1 is important for the development of the embryo overall and that if it’s limited in function, it can also increase the susceptibility to seizures.

However, these patients aren’t missing CRELD1 , they have variations in it: letter changes in the gene that result in changes to the CRELD1 protein but do not cause the protein to completely disappear. When we tested the patient forms of the protein in tadpoles, we found that they did not function the same way as the normal form of CRELD1. Taken together, the clinical and basic science data provides solid evidence that JELANS is a new syndrome caused by variants in the CRELD1 gene.

Is there additional research needed on this syndrome?

Jeffries: As more patients are identified to have JELANS, I think we’ll further refine the clinical syndrome and begin to uncover the molecular mechanisms underlying the symptoms. For instance, we’ll get a better sense of whether the immune system is affected, leading to the increased risk of infection, and how common cardiac dysrhythmias are and what’s the underlying cause.

Why is it important to describe and name a syndrome beyond simply treating the symptoms?

Lakhani: The families of children with undiagnosed diseases frequently go through wandering medical diagnostic odysseys — doctor after doctor, test after test — without ever reaching an answer. Parents can go their entire lives wondering what happened to their child, whether their other children can get the disease, whether they did something to cause it. Knowing a syndrome name and the underlying genetic cause can be so powerful by bringing a sense of closure and relief to families.

Jeffries: It’s validating. It’s clarifying. With a syndrome name, families can find a community and move forward. Especially for rare disorders, in syndrome support groups families can share their stories, discuss what treatments have worked and what treatments haven’t, and just talk to other parents who understand.

Lakhani: And in some countries, it can be hard to get resources without a specific diagnosis. With a diagnosis, families may qualify for support services, so it can have practical implications even beyond the knowledge.

In this case, how will the discovery inform treatment?

Jeffries: Understanding this syndrome at the molecular level is essential for the ultimate goal of finding treatment that’s targeted and specific to this disorder and that is meaningful in helping patients thrive.

Is this an approach others can use?

Lakhani: Everyone who cares for patients should be thinking about this. For many years, as physicians we would look at certain patients and say, “They’ve got something underlying.” But we could never put our finger on it because we didn’t have a robust way to test broadly for genetic conditions; we had to just do the best we could. But we now have a tool that allows us to see if there’s a genetic explanation for a child’s condition. We no longer have to just do the best we can with limited information. We can actually try to find answers. It’s something that has had an incredible impact and it’s something we regularly encourage others to pursue.

Jeffries: And while the discovery of JELANS was through a research endeavor, we want to be clear that DNA sequencing is not just for uncovering new syndromes. Genetic testing can be ordered by a doctor and is available for patients with all sorts of descriptive diagnoses, such as autism, intellectual disability, epilepsy, and cerebral palsy, where symptoms determine the diagnosis.

A patient’s genes may reveal a more specific diagnosis than any constellation of symptoms can define; understanding the molecular cause can ultimately give patients clearer answers and, hopefully, more targeted treatments.

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Research Process

Dissertation markers expect you to include the explanation of research process in methodology chapter. A typical research process comprises the following stages:

1. Selecting the research area . Your dissertation marker expects you to state that you have selected the research area due to professional and personal interests in the area and this statement must be true. Students often underestimate the importance of this first stage in the research process. If you find a research area and research problem that is genuinely interesting to you it is for sure that the whole process of writing your dissertation will be much easier. Therefore, it is never too early to start thinking about the research area for your dissertation.

2. Formulating research aim, objectives and research questions or developing hypotheses . The choice between the formulation of research questions and the development of hypotheses depends on your research approach as it is discussed further below in more details. Appropriate research aims and objectives or hypotheses usually result from several attempts and revisions.

Accordingly, you need to mention in your dissertation that you have revised your research aims and objectives or hypotheses during the research process several times to get their final versions. It is critically important that you get confirmation from your supervisor regarding your research questions or hypotheses before moving forward with the work.

3. Conducting the literature review . Literature review is usually the longest stage in the research process. Actually, the literature review starts even before the formulation of research aims and objective. This is because you have to check if exactly the same research problem has been addressed before and this task is a part of the literature review. Nevertheless, you will conduct the main part of the literature review after the formulation of research aim and objectives. You have to use a wide range of secondary data sources such as books, newspapers, magazines, journals, online articles etc.

4. Selecting data collection methods . Data collection method(s) need to be selected on the basis of critically analyzing advantages and disadvantages associated with several alternative methods. In studies involving primary data collection, you need to write about advantages and disadvantages of selected primary data collection method(s) in detailed manner in methodology.

5. Collecting the primary data . You will have to start primary data collection only after detailed preparation. Sampling is an important element of this stage. You may have to conduct pilot data collection if you chose questionnaire primary data collection method. Primary data collection is not a compulsory stage for all dissertations and you will skip this stage if you are conducting a desk-based research.

6. Data analysis . Analysis of data plays an important role in the achievement of research aim and objectives. This stage involves an extensive editing and coding of data. Data analysis methods vary between secondary and primary studies, as well as, between qualitative and quantitative studies. In data analysis coding of primary data plays an instrumental role to reduce sample group responses to a more manageable form for storage and future processing. Data analysis is discussed in Chapter 6 in great details.

7. Reaching conclusions . Conclusions relate to the level of achievement of research aims and objectives. In this final part of your dissertation you will have to justify why you think that research aims and objectives have been achieved. Conclusions also need to cover research limitations and suggestions for future research .

8. Completing the research . Following all of the stages described above, and organizing separate chapters into one file leads to the completion of the first draft. You need to prepare the first draft of your dissertation at least one month before the submission deadline. This is because you will need to have sufficient amount of time to address feedback to be provided by your supervisor.

Individual stages in the research process outlined above are interdependent and the sequence has to be maintained. Moreover, the process of any research tends to be iterative, meaning that you may have to return back to the previous stages of the research process several times for revisions and improvement. In other words, no stage of the research process is fully completed until the whole dissertation is completed.

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• Americans’ Views of Government’s Role: Persistent Divisions and Areas of Agreement

Wide majorities of Biden and Trump supporters oppose cuts to Social Security

Table of contents.

• Views on the efficiency of government
• Views on the government’s regulation of business
• Confidence in the nation’s ability to solve problems
• Views on the effect of government aid to the poor
• Views on government’s role in health care
• Views on the future of Social Security
• Trust in government
• Feelings toward the federal government
• Acknowledgments
• The American Trends Panel survey methodology

Pew Research Center conducted this study to understand Americans’ attitudes about U.S. government, such as its size and role.

This report is based primarily on a survey of 8,709 adults, including 7,166 registered voters, from April 8 to 14, 2024. Some of the analysis in this report is based on a survey of 8,638 adults from May 13 to 19, 2024.

Everyone who took part in these surveys is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the ATP’s methodology .

Here are the questions used for the report and its methodology .

While the economy, immigration and abortion have emerged as major issues in the 2024 election, Joe Biden and Donald Trump also have dramatically different ideas about the size and role of government.

These differences reflect decades-old divisions between Democrats and Republicans over the scope of government.

Among registered voters, large majorities of Biden supporters – roughly three-quarters or more – favor a bigger, more activist government.

• 74% say they would rather have a bigger government providing more services.
• 76% say government should do more to solve problems.
• 80% say government aid to the poor “does more good than harm.”

Trump supporters, by comparable margins, take the opposing view on all three questions.

The Pew Research Center survey of 8,709 adults – including 7,166 registered voters – conducted April 8-14, 2024, examines Americans’ views of the role and scope of government , the social safety net and long-term trends in trust in the federal government .

Democratic support for bigger government is little changed in the last five years but remains higher than it was a decade ago. Republicans’ views have shifted less over the last 10 years.

Among all adults, about three-quarters of Democrats and Democratic-leaning independents favor a bigger government, up from about six-in-ten in 2014 and 2015. The share of Republicans and Republican leaners who prefer a bigger government has increased only modestly over the same period.

Democratic support for bigger government, while slightly lower than in 2021 (78%), remains at nearly its highest level in five decades. During Bill Clinton’s presidency in the 1990s, fewer than half of Democrats said they preferred a bigger government with more services.

Voters continue to express very different views about government’s role in specific areas than about the government generally.

A large majority of voters (80%) – including 82% of Biden supporters and 78% of Trump supporters – say that in thinking about the long-term future of Social Security, benefits should not be reduced in any way.

However, Biden supporters are more likely than Trump supporters to say Social Security should cover more people with greater benefits.

• 46% of Biden supporters favor expanding Social Security coverage and benefits, compared with 28% of Trump supporters.

Most Americans (65%) continue to say the federal government has a responsibility to make sure all Americans have health care coverage.

Democrats overwhelmingly (88%) say the federal government has this responsibility, compared with 40% of Republicans.

The share of Republicans who say the government has a responsibility to provide health coverage has increased 8 percentage points since 2021, from 32% to 40%.

There are wide income differences among Republicans in opinions about the government’s role in health care:

• 56% of Republicans with lower family incomes say the government has a responsibility to provide health coverage for all, compared with 36% of those with middle incomes and 29% of higher-income Republicans.

When asked how the government should provide health coverage, 36% of Americans say it should be provided through a single national program, while 28% say it should be through a mix of government and private programs. These views have changed little in recent years.

Democrats continue to be more likely than Republicans to favor a “single payer” government health insurance program (53% vs. 18%).

Other key findings in this report

• Americans’ trust in the federal government remains low but has modestly increased since last year. Today, 22% of American adults say they trust the government to do what is right always or most of the time, which is up from 16% in June 2023.
• While the public overall is divided over the nation’s ability to solve important problems, young adults are notably pessimistic about the country’s ability to solve problems . About half of Americans (52%) say the U.S. can’t solve many of its important problems, while 47% say it can find a way to solve problems and get what it wants. Roughly six-in-ten adults under age 30 (62%) say the nation can’t solve major problems, the highest share in any age group and 16 points higher than two years ago.

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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

• Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
• Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
• Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
• Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
• Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
• Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
• Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
• References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

• Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
• Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
• Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
• Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
• Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
• Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
• Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

• Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
• Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
• Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
• Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
• Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
• Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
• Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

• Providing a clear and concise plan of action for the research study.
• Ensuring that the research is conducted ethically and with rigor.
• Maximizing the accuracy and reliability of the research findings.
• Minimizing the possibility of errors, biases, or confounding variables.
• Ensuring that the research is feasible, practical, and cost-effective.
• Determining the appropriate research methodology to answer the research question(s).
• Identifying the sample size, sampling method, and data collection techniques.
• Determining the data analysis method and statistical tests to be used.
• Facilitating the replication of the study by other researchers.
• Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

• Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
• Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
• Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
• Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
• Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

• Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
• Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
• Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
• Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
• Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
• Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
• Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Human health, tourism, and nature

Studying the Relationship Between Tourism and Mosquito-Borne Diseases

 Interviewing Elizabeth Pellecer Rivera, PhD candidate at the University of Maine

[ Español ]

1. Can you tell us a bit about your personal background and how you started your PhD at the University of Maine?

Prior to starting my PhD, I studied sustainable tourism and development studies. Most of my professional experience focused on applied social science research with the Center for Health Studies, at the Universidad del Valle de Guatemala. I worked on researching vector-borne diseases from ecological, biological, and social approaches. This experience made me realize how complex and multifactorial problems are, and how interdisciplinary research can help inform and seek potential solutions. I had the privilege of working on a project related to the Zika virus during its initial emergence in the Americas.

When I learned about the opportunity to work on an interdisciplinary research project about the relationship between tourism and mosquito-borne diseases at the University of Maine, I was thrilled because it touched on many aspects of my personal and academic background. Hopefully this research project will have a positive impact in the public health and tourism sectors.

2. What is your project about and why is it important?

The project aims to provide insight into the dynamics between tourism and emerging diseases, as the world is more interconnected than ever, and tourism and travel represent a large part of human mobility. This project aims to better understand how travel can serve as a driver to spread diseases, how humans perceive the risk of emerging diseases, and what kind of actions and responses they take when facing this kind of risk. Originally the project focused on two mosquito-borne diseases, Zika and chikungunya, but given the extent of impact that the COVID-19 pandemic had, we have included it in the research.

The trends show that international tourism was steadily growing before 2020, and it is expected that outbreaks of emerging diseases will continue occurring. Understanding past experiences can only allow us to better prepare for future events. 

3. What questions did you set out to answer?

My central research questions are:

• What preventative and travel behaviors are being suggested in newsprint media targeting visitors?
• What business strategies, if any, have stakeholders used to respond to the threat that Zika and/or chikungunya, and COVID-19 pose to their business, and their clients?
• How do travelers perceive the potential risk of exposure to Zika, chikungunya or COVID-19 when traveling? What factors influence their risk perception?

With all the data we have gathered, most of our questions are being answered, and new questions have emerged. The challenge is to bring it all together and transform it into useful information for both academics and practitioners.

4. Could you share insights into your research methodology?

The social science part of the research focuses on doing a case study in Guatemala to understand the topic, from diverse perspectives: (1) what is being communicated in the news; (2) what are the travelers’ risk perceptions towards the diseases and what kind of travel-related and preventive actions they tend to adopt; and (3) how the tourism industry has been impacted and what coping and response strategies have they implemented. I am using mixed methods (quantitative and qualitative), including content analysis, surveys, and phenomenological interviews. 

5. What have you discovered so far?

Although my analysis is ongoing, my research has already revealed some interesting findings.We found that news media don’t necessarily balance the messages being communicated. More news included risk-elevating messages, focusing on the “scary” side of the diseases, but did not include as many messages that inform people what to do and how to prevent the diseases. From the tourism stakeholders’ perspective, we have identified some of the main strategies used to cope with mosquito-borne diseases and COVID-19, as well as some of the enabling and limiting factors to overcome the impact of these health-related risks.

6. What were some key challenges and highlights that you have encountered while conducting research?

One of the major challenges has been doing a PhD during the COVID-19 pandemic. The impact of this situation was twofold — it not only induced stress and isolation but also disrupted our initial research plans. We had intended to conduct international research, but the imposition of travel restrictions made it unfeasible. Much of my research had to be conducted virtually.

My favorite part of doing research is interacting with people and being able to listen and learn from their experiences. Therefore, I really enjoyed conducting qualitative interviews, and hearing from the tourism sector about their resilience and capacity to adapt when facing threats like mosquito-borne diseases and COVID-19, especially as the latter impacted the sector as never before. I found it surprising that some individuals pointed out positive outcomes resulting from the pandemic, such as the catalyzation of local organization among stakeholders at destinations and an enhanced appreciation for nature and green spaces among visitors. In conclusion, I was amazed by the diversity of responses and the high degree of optimism and hope.

7. How do you envision the practical applications or real-world impact of your research?

I think the COVID-19 pandemic opened everyone’s eyes to the extent of impact and spread of an emerging disease, both as a public health issue and because it halted human mobility. An integral practical application of my project is to promote intersectoral and interinstitutional relationships, public-private partnerships, academia-practitioner collaborations, and tourism-public health interactions. Overall, my investigation can improve understanding of the intricate relationship between tourism and disease.  

To learn more about my work, read my recent publication :

Elizabeth Pellecer Rivera, Sandra De Urioste-Stone, Laura N. Rickard, Andrea Caprara & Lorena N. Estrada (2024) Tourists and epidemics: how news media cover the risks of Zika virus and chikungunya outbreaks in the Americas, Current Issues in Tourism , DOI: 10.1080/13683500.2024.2309164

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