how to write related studies in quantitative research

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Exploring the literature review 

Literature review model: 6 steps.

Adapted from The Literature Review , Machi & McEvoy (2009, p. 13).

Your Literature Review

Step 2: search, boolean search strategies, search limiters, ★ ebsco & google drive.

1. Select a Topic

"All research begins with curiosity" (Machi & McEvoy, 2009, p. 14)

Selection of a topic, and fully defined research interest and question, is supervised (and approved) by your professor. Tips for crafting your topic include:

• Be specific. Take time to define your interest.
• Topic Focus. Fully describe and sufficiently narrow the focus for research.
• Academic Discipline. Learn more about your area of research & refine the scope.
• Avoid Bias. Be aware of bias that you (as a researcher) may have.
• Document your research. Use Google Docs to track your research process.
• Research apps. Consider using Evernote or Zotero to track your research.

Consider Purpose

What will your topic and research address?

In The Literature Review: A Step-by-Step Guide for Students , Ridley presents that literature reviews serve several purposes (2008, p. 16-17).  Included are the following points:

• Historical background for the research;
• Overview of current field provided by "contemporary debates, issues, and questions;"
• Theories and concepts related to your research;
• Introduce "relevant terminology" - or academic language - being used it the field;
• Connect to existing research - does your work "extend or challenge [this] or address a gap;" 
• Provide "supporting evidence for a practical problem or issue" that your research addresses.

★ Schedule a research appointment

At this point in your literature review, take time to meet with a librarian. Why? Understanding the subject terminology used in databases can be challenging. Archer Librarians can help you structure a search, preparing you for step two. How? Contact a librarian directly or use the online form to schedule an appointment. Details are provided in the adjacent Schedule an Appointment box.

2. Search the Literature

Collect & Select Data: Preview, select, and organize

Archer Library is your go-to resource for this step in your literature review process. The literature search will include books and ebooks, scholarly and practitioner journals, theses and dissertations, and indexes. You may also choose to include web sites, blogs, open access resources, and newspapers. This library guide provides access to resources needed to complete a literature review.

Books & eBooks: Archer Library & OhioLINK

Databases: scholarly & practitioner journals.

Review the Library Databases tab on this library guide, it provides links to recommended databases for Education & Psychology, Business, and General & Social Sciences.

Expand your journal search; a complete listing of available AU Library and OhioLINK databases is available on the Databases  A to Z list . Search the database by subject, type, name, or do use the search box for a general title search. The A to Z list also includes open access resources and select internet sites.

Databases: Theses & Dissertations

Review the Library Databases tab on this guide, it includes Theses & Dissertation resources. AU library also has AU student authored theses and dissertations available in print, search the library catalog for these titles.

Did you know? If you are looking for particular chapters within a dissertation that is not fully available online, it is possible to submit an ILL article request . Do this instead of requesting the entire dissertation.

Newspapers:  Databases & Internet

Consider current literature in your academic field. AU Library's database collection includes The Chronicle of Higher Education and The Wall Street Journal .  The Internet Resources tab in this guide provides links to newspapers and online journals such as Inside Higher Ed , COABE Journal , and Education Week .

Search Strategies & Boolean Operators

There are three basic boolean operators:  AND, OR, and NOT.

Used with your search terms, boolean operators will either expand or limit results. What purpose do they serve? They help to define the relationship between your search terms. For example, using the operator AND will combine the terms expanding the search. When searching some databases, and Google, the operator AND may be implied.

Overview of boolean terms

About the example: Boolean searches were conducted on November 4, 2019; result numbers may vary at a later date. No additional database limiters were set to further narrow search returns.

Database Search Limiters

Database strategies for targeted search results.

Most databases include limiters, or additional parameters, you may use to strategically focus search results.  EBSCO databases, such as Education Research Complete & Academic Search Complete provide options to:

• Limit results to full text;
• Limit results to scholarly journals, and reference available;
• Select results source type to journals, magazines, conference papers, reviews, and newspapers
• Publication date

Keep in mind that these tools are defined as limiters for a reason; adding them to a search will limit the number of results returned.  This can be a double-edged sword.  How? 

• If limiting results to full-text only, you may miss an important piece of research that could change the direction of your research. Interlibrary loan is available to students, free of charge. Request articles that are not available in full-text; they will be sent to you via email.
• If narrowing publication date, you may eliminate significant historical - or recent - research conducted on your topic.
• Limiting resource type to a specific type of material may cause bias in the research results.

Use limiters with care. When starting a search, consider opting out of limiters until the initial literature screening is complete. The second or third time through your research may be the ideal time to focus on specific time periods or material (scholarly vs newspaper).

★ Truncating Search Terms

Expanding your search term at the root.

Truncating is often referred to as 'wildcard' searching. Databases may have their own specific wildcard elements however, the most commonly used are the asterisk (*) or question mark (?).  When used within your search. they will expand returned results.

Asterisk (*) Wildcard

Using the asterisk wildcard will return varied spellings of the truncated word. In the following example, the search term education was truncated after the letter "t."

Explore these database help pages for additional information on crafting search terms.

• EBSCO Connect: Basic Searching with EBSCO
• EBSCO Connect: Searching with Boolean Operators
• EBSCO Connect: Searching with Wildcards and Truncation Symbols
• ProQuest Help: Search Tips
• ERIC: How does ERIC search work?

★ EBSCO Databases & Google Drive

Tips for saving research directly to Google drive.

Researching in an EBSCO database?

It is possible to save articles (PDF and HTML) and abstracts in EBSCOhost databases directly to Google drive. Select the Google Drive icon, authenticate using a Google account, and an EBSCO folder will be created in your account. This is a great option for managing your research. If documenting your research in a Google Doc, consider linking the information to actual articles saved in drive.

EBSCO Databases & Google Drive

EBSCOHost Databases & Google Drive: Managing your Research

This video features an overview of how to use Google Drive with EBSCO databases to help manage your research. It presents information for connecting an active Google account to EBSCO and steps needed to provide permission for EBSCO to manage a folder in Drive.

About the Video:  Closed captioning is available, select CC from the video menu.  If you need to review a specific area on the video, view on YouTube and expand the video description for access to topic time stamps.  A video transcript is provided below.

• EBSCOhost Databases & Google Scholar

Defining Literature Review

What is a literature review.

A definition from the Online Dictionary for Library and Information Sciences .

A literature review is "a comprehensive survey of the works published in a particular field of study or line of research, usually over a specific period of time, in the form of an in-depth, critical bibliographic essay or annotated list in which attention is drawn to the most significant works" (Reitz, 2014). 

A systemic review is "a literature review focused on a specific research question, which uses explicit methods to minimize bias in the identification, appraisal, selection, and synthesis of all the high-quality evidence pertinent to the question" (Reitz, 2014).

Recommended Reading

About this page

EBSCO Connect [Discovery and Search]. (2022). Searching with boolean operators. Retrieved May, 3, 2022 from https://connect.ebsco.com/s/?language=en_US

EBSCO Connect [Discover and Search]. (2022). Searching with wildcards and truncation symbols. Retrieved May 3, 2022; https://connect.ebsco.com/s/?language=en_US

Machi, L.A. & McEvoy, B.T. (2009). The literature review . Thousand Oaks, CA: Corwin Press: 

Reitz, J.M. (2014). Online dictionary for library and information science. ABC-CLIO, Libraries Unlimited . Retrieved from https://www.abc-clio.com/ODLIS/odlis_A.aspx

Ridley, D. (2008). The literature review: A step-by-step guide for students . Thousand Oaks, CA: Sage Publications, Inc.

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This article has a correction. Please see:

• Correction: How to appraise quantitative research - April 01, 2019

• Xabi Cathala 1 ,
• Calvin Moorley 2
• 1 Institute of Vocational Learning , School of Health and Social Care, London South Bank University , London , UK
• 2 Nursing Research and Diversity in Care , School of Health and Social Care, London South Bank University , London , UK
• Correspondence to Mr Xabi Cathala, Institute of Vocational Learning, School of Health and Social Care, London South Bank University London UK ; cathalax{at}lsbu.ac.uk and Dr Calvin Moorley, Nursing Research and Diversity in Care, School of Health and Social Care, London South Bank University, London SE1 0AA, UK; Moorleyc{at}lsbu.ac.uk

https://doi.org/10.1136/eb-2018-102996

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Introduction

Some nurses feel that they lack the necessary skills to read a research paper and to then decide if they should implement the findings into their practice. This is particularly the case when considering the results of quantitative research, which often contains the results of statistical testing. However, nurses have a professional responsibility to critique research to improve their practice, care and patient safety. 1  This article provides a step by step guide on how to critically appraise a quantitative paper.

Title, keywords and the authors

The authors’ names may not mean much, but knowing the following will be helpful:

Their position, for example, academic, researcher or healthcare practitioner.

Their qualification, both professional, for example, a nurse or physiotherapist and academic (eg, degree, masters, doctorate).

This can indicate how the research has been conducted and the authors’ competence on the subject. Basically, do you want to read a paper on quantum physics written by a plumber?

The abstract is a resume of the article and should contain:

Introduction.

Research question/hypothesis.

Methods including sample design, tests used and the statistical analysis (of course! Remember we love numbers).

Main findings.

Conclusion.

The subheadings in the abstract will vary depending on the journal. An abstract should not usually be more than 300 words but this varies depending on specific journal requirements. If the above information is contained in the abstract, it can give you an idea about whether the study is relevant to your area of practice. However, before deciding if the results of a research paper are relevant to your practice, it is important to review the overall quality of the article. This can only be done by reading and critically appraising the entire article.

The introduction

Example: the effect of paracetamol on levels of pain.

My hypothesis is that A has an effect on B, for example, paracetamol has an effect on levels of pain.

My null hypothesis is that A has no effect on B, for example, paracetamol has no effect on pain.

My study will test the null hypothesis and if the null hypothesis is validated then the hypothesis is false (A has no effect on B). This means paracetamol has no effect on the level of pain. If the null hypothesis is rejected then the hypothesis is true (A has an effect on B). This means that paracetamol has an effect on the level of pain.

Background/literature review

The literature review should include reference to recent and relevant research in the area. It should summarise what is already known about the topic and why the research study is needed and state what the study will contribute to new knowledge. 5 The literature review should be up to date, usually 5–8 years, but it will depend on the topic and sometimes it is acceptable to include older (seminal) studies.

Methodology

In quantitative studies, the data analysis varies between studies depending on the type of design used. For example, descriptive, correlative or experimental studies all vary. A descriptive study will describe the pattern of a topic related to one or more variable. 6 A correlational study examines the link (correlation) between two variables 7  and focuses on how a variable will react to a change of another variable. In experimental studies, the researchers manipulate variables looking at outcomes 8  and the sample is commonly assigned into different groups (known as randomisation) to determine the effect (causal) of a condition (independent variable) on a certain outcome. This is a common method used in clinical trials.

There should be sufficient detail provided in the methods section for you to replicate the study (should you want to). To enable you to do this, the following sections are normally included:

Overview and rationale for the methodology.

Participants or sample.

Data collection tools.

Methods of data analysis.

Ethical issues.

Data collection should be clearly explained and the article should discuss how this process was undertaken. Data collection should be systematic, objective, precise, repeatable, valid and reliable. Any tool (eg, a questionnaire) used for data collection should have been piloted (or pretested and/or adjusted) to ensure the quality, validity and reliability of the tool. 9 The participants (the sample) and any randomisation technique used should be identified. The sample size is central in quantitative research, as the findings should be able to be generalised for the wider population. 10 The data analysis can be done manually or more complex analyses performed using computer software sometimes with advice of a statistician. From this analysis, results like mode, mean, median, p value, CI and so on are always presented in a numerical format.

The author(s) should present the results clearly. These may be presented in graphs, charts or tables alongside some text. You should perform your own critique of the data analysis process; just because a paper has been published, it does not mean it is perfect. Your findings may be different from the author’s. Through critical analysis the reader may find an error in the study process that authors have not seen or highlighted. These errors can change the study result or change a study you thought was strong to weak. To help you critique a quantitative research paper, some guidance on understanding statistical terminology is provided in  table 1 .

• View inline

Some basic guidance for understanding statistics

Quantitative studies examine the relationship between variables, and the p value illustrates this objectively.  11  If the p value is less than 0.05, the null hypothesis is rejected and the hypothesis is accepted and the study will say there is a significant difference. If the p value is more than 0.05, the null hypothesis is accepted then the hypothesis is rejected. The study will say there is no significant difference. As a general rule, a p value of less than 0.05 means, the hypothesis is accepted and if it is more than 0.05 the hypothesis is rejected.

The CI is a number between 0 and 1 or is written as a per cent, demonstrating the level of confidence the reader can have in the result. 12  The CI is calculated by subtracting the p value to 1 (1–p). If there is a p value of 0.05, the CI will be 1–0.05=0.95=95%. A CI over 95% means, we can be confident the result is statistically significant. A CI below 95% means, the result is not statistically significant. The p values and CI highlight the confidence and robustness of a result.

Discussion, recommendations and conclusion

The final section of the paper is where the authors discuss their results and link them to other literature in the area (some of which may have been included in the literature review at the start of the paper). This reminds the reader of what is already known, what the study has found and what new information it adds. The discussion should demonstrate how the authors interpreted their results and how they contribute to new knowledge in the area. Implications for practice and future research should also be highlighted in this section of the paper.

A few other areas you may find helpful are:

Limitations of the study.

Conflicts of interest.

Table 2 provides a useful tool to help you apply the learning in this paper to the critiquing of quantitative research papers.

Quantitative paper appraisal checklist

• 1. ↵ Nursing and Midwifery Council , 2015 . The code: standard of conduct, performance and ethics for nurses and midwives https://www.nmc.org.uk/globalassets/sitedocuments/nmc-publications/nmc-code.pdf ( accessed 21.8.18 ).
• Gerrish K ,
• Moorley C ,
• Tunariu A , et al
• Shorten A ,

Competing interests None declared.

Patient consent Not required.

Provenance and peer review Commissioned; internally peer reviewed.

Correction notice This article has been updated since its original publication to update p values from 0.5 to 0.05 throughout.

Linked Articles

• Miscellaneous Correction: How to appraise quantitative research BMJ Publishing Group Ltd and RCN Publishing Company Ltd Evidence-Based Nursing 2019; 22 62-62 Published Online First: 31 Jan 2019. doi: 10.1136/eb-2018-102996corr1

Read the full text or download the PDF:

Writing Quantitative Research Studies

• Reference work entry
• First Online: 13 January 2019
• Cite this reference work entry

• Ankur Singh 2 ,
• Adyya Gupta 3 &
• Karen G. Peres 4  

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Summarizing quantitative data and its effective presentation and discussion can be challenging for students and researchers. This chapter provides a framework for adequately reporting findings from quantitative analysis in a research study for those contemplating to write a research paper. The rationale underpinning the reporting methods to maintain the credibility and integrity of quantitative studies is outlined. Commonly used terminologies in empirical studies are defined and discussed with suitable examples. Key elements that build consistency between different sections (background, methods, results, and the discussion) of a research study using quantitative methods in a journal article are explicated. Specifically, recommended standard guidelines for randomized controlled trials and observational studies for reporting and discussion of findings from quantitative studies are elaborated. Key aspects of methodology that include describing the study population, sampling strategy, data collection methods, measurements/variables, and statistical analysis which informs the quality of a study from the reviewer’s perspective are described. Effective use of references in the methods section to strengthen the rationale behind specific statistical techniques and choice of measures has been highlighted with examples. Identifying ways in which data can be most succinctly and effectively summarized in tables and graphs according to their suitability and purpose of information is also detailed in this chapter. Strategies to present and discuss the quantitative findings in a structured discussion section are also provided. Overall, the chapter provides the readers with a comprehensive set of tools to identify key strategies to be considered when reporting quantitative research.

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Authors and affiliations.

Centre for Health Equity, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia

Ankur Singh

School of Public Health, The University of Adelaide, Adelaide, SA, Australia

Adyya Gupta

Australian Research Centre for Population Oral Health (ARCPOH), Adelaide Dental School, The University of Adelaide, Adelaide, SA, Australia

Karen G. Peres

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Correspondence to Ankur Singh .

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School of Science and Health, Western Sydney University, Penrith, NSW, Australia

Pranee Liamputtong

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Singh, A., Gupta, A., Peres, K.G. (2019). Writing Quantitative Research Studies. In: Liamputtong, P. (eds) Handbook of Research Methods in Health Social Sciences. Springer, Singapore. https://doi.org/10.1007/978-981-10-5251-4_117

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How To Write The Results/Findings Chapter

For quantitative studies (dissertations & theses).

By: Derek Jansen (MBA). Expert Reviewed By: Kerryn Warren (PhD) | July 2021

So, you’ve completed your quantitative data analysis and it’s time to report on your findings. But where do you start? In this post, we’ll walk you through the results chapter (also called the findings or analysis chapter), step by step, so that you can craft this section of your dissertation or thesis with confidence. If you’re looking for information regarding the results chapter for qualitative studies, you can find that here .

Overview: Quantitative Results Chapter

• What exactly the results/findings/analysis chapter is
• What you need to include in your results chapter
• How to structure your results chapter
• A few tips and tricks for writing top-notch chapter

What exactly is the results chapter?

The results chapter (also referred to as the findings or analysis chapter) is one of the most important chapters of your dissertation or thesis because it shows the reader what you’ve found in terms of the quantitative data you’ve collected. It presents the data using a clear text narrative, supported by tables, graphs and charts. In doing so, it also highlights any potential issues (such as outliers or unusual findings) you’ve come across.

But how’s that different from the discussion chapter?

Well, in the results chapter, you only present your statistical findings. Only the numbers, so to speak – no more, no less. Contrasted to this, in the discussion chapter , you interpret your findings and link them to prior research (i.e. your literature review), as well as your research objectives and research questions . In other words, the results chapter presents and describes the data, while the discussion chapter interprets the data.

Let’s look at an example.

In your results chapter, you may have a plot that shows how respondents to a survey  responded: the numbers of respondents per category, for instance. You may also state whether this supports a hypothesis by using a p-value from a statistical test. But it is only in the discussion chapter where you will say why this is relevant or how it compares with the literature or the broader picture. So, in your results chapter, make sure that you don’t present anything other than the hard facts – this is not the place for subjectivity.

It’s worth mentioning that some universities prefer you to combine the results and discussion chapters. Even so, it is good practice to separate the results and discussion elements within the chapter, as this ensures your findings are fully described. Typically, though, the results and discussion chapters are split up in quantitative studies. If you’re unsure, chat with your research supervisor or chair to find out what their preference is.

What should you include in the results chapter?

Following your analysis, it’s likely you’ll have far more data than are necessary to include in your chapter. In all likelihood, you’ll have a mountain of SPSS or R output data, and it’s your job to decide what’s most relevant. You’ll need to cut through the noise and focus on the data that matters.

This doesn’t mean that those analyses were a waste of time – on the contrary, those analyses ensure that you have a good understanding of your dataset and how to interpret it. However, that doesn’t mean your reader or examiner needs to see the 165 histograms you created! Relevance is key.

How do I decide what’s relevant?

At this point, it can be difficult to strike a balance between what is and isn’t important. But the most important thing is to ensure your results reflect and align with the purpose of your study .  So, you need to revisit your research aims, objectives and research questions and use these as a litmus test for relevance. Make sure that you refer back to these constantly when writing up your chapter so that you stay on track.

As a general guide, your results chapter will typically include the following:

• Some demographic data about your sample
• Reliability tests (if you used measurement scales)
• Descriptive statistics
• Inferential statistics (if your research objectives and questions require these)
• Hypothesis tests (again, if your research objectives and questions require these)

We’ll discuss each of these points in more detail in the next section.

Importantly, your results chapter needs to lay the foundation for your discussion chapter . This means that, in your results chapter, you need to include all the data that you will use as the basis for your interpretation in the discussion chapter.

For example, if you plan to highlight the strong relationship between Variable X and Variable Y in your discussion chapter, you need to present the respective analysis in your results chapter – perhaps a correlation or regression analysis.

Need a helping hand?

How do I write the results chapter?

There are multiple steps involved in writing up the results chapter for your quantitative research. The exact number of steps applicable to you will vary from study to study and will depend on the nature of the research aims, objectives and research questions . However, we’ll outline the generic steps below.

Step 1 – Revisit your research questions

The first step in writing your results chapter is to revisit your research objectives and research questions . These will be (or at least, should be!) the driving force behind your results and discussion chapters, so you need to review them and then ask yourself which statistical analyses and tests (from your mountain of data) would specifically help you address these . For each research objective and research question, list the specific piece (or pieces) of analysis that address it.

At this stage, it’s also useful to think about the key points that you want to raise in your discussion chapter and note these down so that you have a clear reminder of which data points and analyses you want to highlight in the results chapter. Again, list your points and then list the specific piece of analysis that addresses each point. 

Next, you should draw up a rough outline of how you plan to structure your chapter . Which analyses and statistical tests will you present and in what order? We’ll discuss the “standard structure” in more detail later, but it’s worth mentioning now that it’s always useful to draw up a rough outline before you start writing (this advice applies to any chapter).

Step 2 – Craft an overview introduction

As with all chapters in your dissertation or thesis, you should start your quantitative results chapter by providing a brief overview of what you’ll do in the chapter and why . For example, you’d explain that you will start by presenting demographic data to understand the representativeness of the sample, before moving onto X, Y and Z.

This section shouldn’t be lengthy – a paragraph or two maximum. Also, it’s a good idea to weave the research questions into this section so that there’s a golden thread that runs through the document.

Step 3 – Present the sample demographic data

The first set of data that you’ll present is an overview of the sample demographics – in other words, the demographics of your respondents.

For example:

• What age range are they?
• How is gender distributed?
• How is ethnicity distributed?
• What areas do the participants live in?

The purpose of this is to assess how representative the sample is of the broader population. This is important for the sake of the generalisability of the results. If your sample is not representative of the population, you will not be able to generalise your findings. This is not necessarily the end of the world, but it is a limitation you’ll need to acknowledge.

Of course, to make this representativeness assessment, you’ll need to have a clear view of the demographics of the population. So, make sure that you design your survey to capture the correct demographic information that you will compare your sample to.

But what if I’m not interested in generalisability?

Well, even if your purpose is not necessarily to extrapolate your findings to the broader population, understanding your sample will allow you to interpret your findings appropriately, considering who responded. In other words, it will help you contextualise your findings . For example, if 80% of your sample was aged over 65, this may be a significant contextual factor to consider when interpreting the data. Therefore, it’s important to understand and present the demographic data.

 Step 4 – Review composite measures and the data “shape”.

Before you undertake any statistical analysis, you’ll need to do some checks to ensure that your data are suitable for the analysis methods and techniques you plan to use. If you try to analyse data that doesn’t meet the assumptions of a specific statistical technique, your results will be largely meaningless. Therefore, you may need to show that the methods and techniques you’ll use are “allowed”.

Most commonly, there are two areas you need to pay attention to:

#1: Composite measures

The first is when you have multiple scale-based measures that combine to capture one construct – this is called a composite measure .  For example, you may have four Likert scale-based measures that (should) all measure the same thing, but in different ways. In other words, in a survey, these four scales should all receive similar ratings. This is called “ internal consistency ”.

Internal consistency is not guaranteed though (especially if you developed the measures yourself), so you need to assess the reliability of each composite measure using a test. Typically, Cronbach’s Alpha is a common test used to assess internal consistency – i.e., to show that the items you’re combining are more or less saying the same thing. A high alpha score means that your measure is internally consistent. A low alpha score means you may need to consider scrapping one or more of the measures.

#2: Data shape

The second matter that you should address early on in your results chapter is data shape. In other words, you need to assess whether the data in your set are symmetrical (i.e. normally distributed) or not, as this will directly impact what type of analyses you can use. For many common inferential tests such as T-tests or ANOVAs (we’ll discuss these a bit later), your data needs to be normally distributed. If it’s not, you’ll need to adjust your strategy and use alternative tests.

To assess the shape of the data, you’ll usually assess a variety of descriptive statistics (such as the mean, median and skewness), which is what we’ll look at next.

Step 5 – Present the descriptive statistics

Now that you’ve laid the foundation by discussing the representativeness of your sample, as well as the reliability of your measures and the shape of your data, you can get started with the actual statistical analysis. The first step is to present the descriptive statistics for your variables.

For scaled data, this usually includes statistics such as:

• The mean – this is simply the mathematical average of a range of numbers.
• The median – this is the midpoint in a range of numbers when the numbers are arranged in order.
• The mode – this is the most commonly repeated number in the data set.
• Standard deviation – this metric indicates how dispersed a range of numbers is. In other words, how close all the numbers are to the mean (the average).
• Skewness – this indicates how symmetrical a range of numbers is. In other words, do they tend to cluster into a smooth bell curve shape in the middle of the graph (this is called a normal or parametric distribution), or do they lean to the left or right (this is called a non-normal or non-parametric distribution).
• Kurtosis – this metric indicates whether the data are heavily or lightly-tailed, relative to the normal distribution. In other words, how peaked or flat the distribution is.

A large table that indicates all the above for multiple variables can be a very effective way to present your data economically. You can also use colour coding to help make the data more easily digestible.

For categorical data, where you show the percentage of people who chose or fit into a category, for instance, you can either just plain describe the percentages or numbers of people who responded to something or use graphs and charts (such as bar graphs and pie charts) to present your data in this section of the chapter.

When using figures, make sure that you label them simply and clearly , so that your reader can easily understand them. There’s nothing more frustrating than a graph that’s missing axis labels! Keep in mind that although you’ll be presenting charts and graphs, your text content needs to present a clear narrative that can stand on its own. In other words, don’t rely purely on your figures and tables to convey your key points: highlight the crucial trends and values in the text. Figures and tables should complement the writing, not carry it .

Depending on your research aims, objectives and research questions, you may stop your analysis at this point (i.e. descriptive statistics). However, if your study requires inferential statistics, then it’s time to deep dive into those .

Step 6 – Present the inferential statistics

Inferential statistics are used to make generalisations about a population , whereas descriptive statistics focus purely on the sample . Inferential statistical techniques, broadly speaking, can be broken down into two groups .

First, there are those that compare measurements between groups , such as t-tests (which measure differences between two groups) and ANOVAs (which measure differences between multiple groups). Second, there are techniques that assess the relationships between variables , such as correlation analysis and regression analysis. Within each of these, some tests can be used for normally distributed (parametric) data and some tests are designed specifically for use on non-parametric data.

There are a seemingly endless number of tests that you can use to crunch your data, so it’s easy to run down a rabbit hole and end up with piles of test data. Ultimately, the most important thing is to make sure that you adopt the tests and techniques that allow you to achieve your research objectives and answer your research questions .

In this section of the results chapter, you should try to make use of figures and visual components as effectively as possible. For example, if you present a correlation table, use colour coding to highlight the significance of the correlation values, or scatterplots to visually demonstrate what the trend is. The easier you make it for your reader to digest your findings, the more effectively you’ll be able to make your arguments in the next chapter.

Step 7 – Test your hypotheses

If your study requires it, the next stage is hypothesis testing. A hypothesis is a statement , often indicating a difference between groups or relationship between variables, that can be supported or rejected by a statistical test. However, not all studies will involve hypotheses (again, it depends on the research objectives), so don’t feel like you “must” present and test hypotheses just because you’re undertaking quantitative research.

The basic process for hypothesis testing is as follows:

• Specify your null hypothesis (for example, “The chemical psilocybin has no effect on time perception).
• Specify your alternative hypothesis (e.g., “The chemical psilocybin has an effect on time perception)
• Set your significance level (this is usually 0.05)
• Calculate your statistics and find your p-value (e.g., p=0.01)
• Draw your conclusions (e.g., “The chemical psilocybin does have an effect on time perception”)

Finally, if the aim of your study is to develop and test a conceptual framework , this is the time to present it, following the testing of your hypotheses. While you don’t need to develop or discuss these findings further in the results chapter, indicating whether the tests (and their p-values) support or reject the hypotheses is crucial.

Step 8 – Provide a chapter summary

To wrap up your results chapter and transition to the discussion chapter, you should provide a brief summary of the key findings . “Brief” is the keyword here – much like the chapter introduction, this shouldn’t be lengthy – a paragraph or two maximum. Highlight the findings most relevant to your research objectives and research questions, and wrap it up.

Some final thoughts, tips and tricks

Now that you’ve got the essentials down, here are a few tips and tricks to make your quantitative results chapter shine:

• When writing your results chapter, report your findings in the past tense . You’re talking about what you’ve found in your data, not what you are currently looking for or trying to find.
• Structure your results chapter systematically and sequentially . If you had two experiments where findings from the one generated inputs into the other, report on them in order.
• Make your own tables and graphs rather than copying and pasting them from statistical analysis programmes like SPSS. Check out the DataIsBeautiful reddit for some inspiration.
• Once you’re done writing, review your work to make sure that you have provided enough information to answer your research questions , but also that you didn’t include superfluous information.

If you’ve got any questions about writing up the quantitative results chapter, please leave a comment below. If you’d like 1-on-1 assistance with your quantitative analysis and discussion, check out our hands-on coaching service , or book a free consultation with a friendly coach.

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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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Thank you. I will try my best to write my results.

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How to Make a Literature Review in Research (RRL Example)

What is an RRL in a research paper?

A relevant review of the literature (RRL) is an objective, concise, critical summary of published research literature relevant to a topic being researched in an article. In an RRL, you discuss knowledge and findings from existing literature relevant to your study topic. If there are conflicts or gaps in existing literature, you can also discuss these in your review, as well as how you will confront these missing elements or resolve these issues in your study.

To complete an RRL, you first need to collect relevant literature; this can include online and offline sources. Save all of your applicable resources as you will need to include them in your paper. When looking through these sources, take notes and identify concepts of each source to describe in the review of the literature.

A good RRL does NOT:

A literature review does not simply reference and list all of the material you have cited in your paper.

• Presenting material that is not directly relevant to your study will distract and frustrate the reader and make them lose sight of the purpose of your study.
• Starting a literature review with “A number of scholars have studied the relationship between X and Y” and simply listing who has studied the topic and what each scholar concluded is not going to strengthen your paper.

A good RRL DOES:

• Present a brief typology that orders articles and books into groups to help readers focus on unresolved debates, inconsistencies, tensions, and new questions about a research topic.
• Summarize the most relevant and important aspects of the scientific literature related to your area of research
• Synthesize what has been done in this area of research and by whom, highlight what previous research indicates about a topic, and identify potential gaps and areas of disagreement in the field
• Give the reader an understanding of the background of the field and show which studies are important—and highlight errors in previous studies

How long is a review of the literature for a research paper?

The length of a review of the literature depends on its purpose and target readership and can vary significantly in scope and depth. In a dissertation, thesis, or standalone review of literature, it is usually a full chapter of the text (at least 20 pages). Whereas, a standard research article or school assignment literature review section could only be a few paragraphs in the Introduction section .

Building Your Literature Review Bookshelf

One way to conceive of a literature review is to think about writing it as you would build a bookshelf. You don’t need to cut each piece by yourself from scratch. Rather, you can take the pieces that other researchers have cut out and put them together to build a framework on which to hang your own “books”—that is, your own study methods, results, and conclusions.

What Makes a Good Literature Review?

The contents of a literature review (RRL) are determined by many factors, including its precise purpose in the article, the degree of consensus with a given theory or tension between competing theories, the length of the article, the number of previous studies existing in the given field, etc. The following are some of the most important elements that a literature review provides.

Historical background for your research

Analyze what has been written about your field of research to highlight what is new and significant in your study—or how the analysis itself contributes to the understanding of this field, even in a small way. Providing a historical background also demonstrates to other researchers and journal editors your competency in discussing theoretical concepts. You should also make sure to understand how to paraphrase scientific literature to avoid plagiarism in your work.

The current context of your research

Discuss central (or peripheral) questions, issues, and debates in the field. Because a field is constantly being updated by new work, you can show where your research fits into this context and explain developments and trends in research.

A discussion of relevant theories and concepts

Theories and concepts should provide the foundation for your research. For example, if you are researching the relationship between ecological environments and human populations, provide models and theories that focus on specific aspects of this connection to contextualize your study. If your study asks a question concerning sustainability, mention a theory or model that underpins this concept. If it concerns invasive species, choose material that is focused in this direction.

Definitions of relevant terminology

In the natural sciences, the meaning of terms is relatively straightforward and consistent. But if you present a term that is obscure or context-specific, you should define the meaning of the term in the Introduction section (if you are introducing a study) or in the summary of the literature being reviewed.

Description of related relevant research

Include a description of related research that shows how your work expands or challenges earlier studies or fills in gaps in previous work. You can use your literature review as evidence of what works, what doesn’t, and what is missing in the field.

Supporting evidence for a practical problem or issue your research is addressing that demonstrates its importance: Referencing related research establishes your area of research as reputable and shows you are building upon previous work that other researchers have deemed significant.

Types of Literature Reviews

Literature reviews can differ in structure, length, amount, and breadth of content included. They can range from selective (a very narrow area of research or only a single work) to comprehensive (a larger amount or range of works). They can also be part of a larger work or stand on their own.

• A course assignment is an example of a selective, stand-alone work. It focuses on a small segment of the literature on a topic and makes up an entire work on its own.
• The literature review in a dissertation or thesis is both comprehensive and helps make up a larger work.
• A majority of journal articles start with a selective literature review to provide context for the research reported in the study; such a literature review is usually included in the Introduction section (but it can also follow the presentation of the results in the Discussion section ).
• Some literature reviews are both comprehensive and stand as a separate work—in this case, the entire article analyzes the literature on a given topic.

Literature Reviews Found in Academic Journals

The two types of literature reviews commonly found in journals are those introducing research articles (studies and surveys) and stand-alone literature analyses. They can differ in their scope, length, and specific purpose.

Literature reviews introducing research articles

The literature review found at the beginning of a journal article is used to introduce research related to the specific study and is found in the Introduction section, usually near the end. It is shorter than a stand-alone review because it must be limited to very specific studies and theories that are directly relevant to the current study. Its purpose is to set research precedence and provide support for the study’s theory, methods, results, and/or conclusions. Not all research articles contain an explicit review of the literature, but most do, whether it is a discrete section or indistinguishable from the rest of the Introduction.

How to structure a literature review for an article

When writing a literature review as part of an introduction to a study, simply follow the structure of the Introduction and move from the general to the specific—presenting the broadest background information about a topic first and then moving to specific studies that support your rationale , finally leading to your hypothesis statement. Such a literature review is often indistinguishable from the Introduction itself—the literature is INTRODUCING the background and defining the gaps your study aims to fill.

The stand-alone literature review

The literature review published as a stand-alone article presents and analyzes as many of the important publications in an area of study as possible to provide background information and context for a current area of research or a study. Stand-alone reviews are an excellent resource for researchers when they are first searching for the most relevant information on an area of study.

Such literature reviews are generally a bit broader in scope and can extend further back in time. This means that sometimes a scientific literature review can be highly theoretical, in addition to focusing on specific methods and outcomes of previous studies. In addition, all sections of such a “review article” refer to existing literature rather than describing the results of the authors’ own study.

In addition, this type of literature review is usually much longer than the literature review introducing a study. At the end of the review follows a conclusion that once again explicitly ties all of the cited works together to show how this analysis is itself a contribution to the literature. While not absolutely necessary, such articles often include the terms “Literature Review” or “Review of the Literature” in the title. Whether or not that is necessary or appropriate can also depend on the specific author instructions of the target journal. Have a look at this article for more input on how to compile a stand-alone review article that is insightful and helpful for other researchers in your field.

How to Write a Literature Review in 6 Steps

So how do authors turn a network of articles into a coherent review of relevant literature?

Writing a literature review is not usually a linear process—authors often go back and check the literature while reformulating their ideas or making adjustments to their study. Sometimes new findings are published before a study is completed and need to be incorporated into the current work. This also means you will not be writing the literature review at any one time, but constantly working on it before, during, and after your study is complete.

Here are some steps that will help you begin and follow through on your literature review.

Step 1: Choose a topic to write about—focus on and explore this topic.

Choose a topic that you are familiar with and highly interested in analyzing; a topic your intended readers and researchers will find interesting and useful; and a topic that is current, well-established in the field, and about which there has been sufficient research conducted for a review. This will help you find the “sweet spot” for what to focus on.

Step 2: Research and collect all the scholarly information on the topic that might be pertinent to your study.

This includes scholarly articles, books, conventions, conferences, dissertations, and theses—these and any other academic work related to your area of study is called “the literature.”

Step 3: Analyze the network of information that extends or responds to the major works in your area; select the material that is most useful.

Use thought maps and charts to identify intersections in the research and to outline important categories; select the material that will be most useful to your review.

Step 4: Describe and summarize each article—provide the essential information of the article that pertains to your study.

Determine 2-3 important concepts (depending on the length of your article) that are discussed in the literature; take notes about all of the important aspects of this study relevant to the topic being reviewed.

For example, in a given study, perhaps some of the main concepts are X, Y, and Z. Note these concepts and then write a brief summary about how the article incorporates them. In reviews that introduce a study, these can be relatively short. In stand-alone reviews, there may be significantly more texts and more concepts.

Step 5: Demonstrate how these concepts in the literature relate to what you discovered in your study or how the literature connects the concepts or topics being discussed.

In a literature review intro for an article, this information might include a summary of the results or methods of previous studies that correspond to and/or confirm those sections in your own study. For a stand-alone literature review, this may mean highlighting the concepts in each article and showing how they strengthen a hypothesis or show a pattern.

Discuss unaddressed issues in previous studies. These studies that are missing something you address are important to include in your literature review. In addition, those works whose theories and conclusions directly support your findings will be valuable to review here.

Step 6: Identify relationships in the literature and develop and connect your own ideas to them.

This is essentially the same as step 5 but focused on the connections between the literature and the current study or guiding concepts or arguments of the paper, not only on the connections between the works themselves.

Your hypothesis, argument, or guiding concept is the “golden thread” that will ultimately tie the works together and provide readers with specific insights they didn’t have before reading your literature review. Make sure you know where to put the research question , hypothesis, or statement of the problem in your research paper so that you guide your readers logically and naturally from your introduction of earlier work and evidence to the conclusions you want them to draw from the bigger picture.

Your literature review will not only cover publications on your topics but will include your own ideas and contributions. By following these steps you will be telling the specific story that sets the background and shows the significance of your research and you can turn a network of related works into a focused review of the literature.

Literature Review (RRL) Examples

Because creating sample literature reviews would take too long and not properly capture the nuances and detailed information needed for a good review, we have included some links to different types of literature reviews below. You can find links to more literature reviews in these categories by visiting the TUS Library’s website . Sample literature reviews as part of an article, dissertation, or thesis:

• Critical Thinking and Transferability: A Review of the Literature (Gwendolyn Reece)
• Building Customer Loyalty: A Customer Experience Based Approach in a Tourism Context (Martina Donnelly)

Sample stand-alone literature reviews

• Literature Review on Attitudes towards Disability (National Disability Authority)
• The Effects of Communication Styles on Marital Satisfaction (Hannah Yager)

Additional Literature Review Format Guidelines

In addition to the content guidelines above, authors also need to check which style guidelines to use ( APA , Chicago, MLA, etc.) and what specific rules the target journal might have for how to structure such articles or how many studies to include—such information can usually be found on the journals’ “Guide for Authors” pages. Additionally, use one of the four Wordvice citation generators below, choosing the citation style needed for your paper:

Wordvice Writing and Academic Editing Resources

Finally, after you have finished drafting your literature review, be sure to receive professional proofreading services , including paper editing for your academic work. A competent proofreader who understands academic writing conventions and the specific style guides used by academic journals will ensure that your paper is ready for publication in your target journal.

See our academic resources for further advice on references in your paper , how to write an abstract , how to write a research paper title, how to impress the editor of your target journal with a perfect cover letter , and dozens of other research writing and publication topics.

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Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques . Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Muijs, Daniel. Doing Quantitative Research in Education with SPSS . 2nd edition. London: SAGE Publications, 2010.

Need Help Locating Statistics?

Resources for locating data and statistics can be found here:

Statistics & Data Research Guide

Characteristics of Quantitative Research

Your goal in conducting quantitative research study is to determine the relationship between one thing [an independent variable] and another [a dependent or outcome variable] within a population. Quantitative research designs are either descriptive [subjects usually measured once] or experimental [subjects measured before and after a treatment]. A descriptive study establishes only associations between variables; an experimental study establishes causality.

Quantitative research deals in numbers, logic, and an objective stance. Quantitative research focuses on numeric and unchanging data and detailed, convergent reasoning rather than divergent reasoning [i.e., the generation of a variety of ideas about a research problem in a spontaneous, free-flowing manner].

Its main characteristics are :

• The data is usually gathered using structured research instruments.
• The results are based on larger sample sizes that are representative of the population.
• The research study can usually be replicated or repeated, given its high reliability.
• Researcher has a clearly defined research question to which objective answers are sought.
• All aspects of the study are carefully designed before data is collected.
• Data are in the form of numbers and statistics, often arranged in tables, charts, figures, or other non-textual forms.
• Project can be used to generalize concepts more widely, predict future results, or investigate causal relationships.
• Researcher uses tools, such as questionnaires or computer software, to collect numerical data.

The overarching aim of a quantitative research study is to classify features, count them, and construct statistical models in an attempt to explain what is observed.

  Things to keep in mind when reporting the results of a study using quantitative methods :

• Explain the data collected and their statistical treatment as well as all relevant results in relation to the research problem you are investigating. Interpretation of results is not appropriate in this section.
• Report unanticipated events that occurred during your data collection. Explain how the actual analysis differs from the planned analysis. Explain your handling of missing data and why any missing data does not undermine the validity of your analysis.
• Explain the techniques you used to "clean" your data set.
• Choose a minimally sufficient statistical procedure ; provide a rationale for its use and a reference for it. Specify any computer programs used.
• Describe the assumptions for each procedure and the steps you took to ensure that they were not violated.
• When using inferential statistics , provide the descriptive statistics, confidence intervals, and sample sizes for each variable as well as the value of the test statistic, its direction, the degrees of freedom, and the significance level [report the actual p value].
• Avoid inferring causality , particularly in nonrandomized designs or without further experimentation.
• Use tables to provide exact values ; use figures to convey global effects. Keep figures small in size; include graphic representations of confidence intervals whenever possible.
• Always tell the reader what to look for in tables and figures .

NOTE:   When using pre-existing statistical data gathered and made available by anyone other than yourself [e.g., government agency], you still must report on the methods that were used to gather the data and describe any missing data that exists and, if there is any, provide a clear explanation why the missing data does not undermine the validity of your final analysis.

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Quantitative Research Methods. Writing@CSU. Colorado State University; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Basic Research Design for Quantitative Studies

Before designing a quantitative research study, you must decide whether it will be descriptive or experimental because this will dictate how you gather, analyze, and interpret the results. A descriptive study is governed by the following rules: subjects are generally measured once; the intention is to only establish associations between variables; and, the study may include a sample population of hundreds or thousands of subjects to ensure that a valid estimate of a generalized relationship between variables has been obtained. An experimental design includes subjects measured before and after a particular treatment, the sample population may be very small and purposefully chosen, and it is intended to establish causality between variables. Introduction The introduction to a quantitative study is usually written in the present tense and from the third person point of view. It covers the following information:

• Identifies the research problem -- as with any academic study, you must state clearly and concisely the research problem being investigated.
• Reviews the literature -- review scholarship on the topic, synthesizing key themes and, if necessary, noting studies that have used similar methods of inquiry and analysis. Note where key gaps exist and how your study helps to fill these gaps or clarifies existing knowledge.
• Describes the theoretical framework -- provide an outline of the theory or hypothesis underpinning your study. If necessary, define unfamiliar or complex terms, concepts, or ideas and provide the appropriate background information to place the research problem in proper context [e.g., historical, cultural, economic, etc.].

Methodology The methods section of a quantitative study should describe how each objective of your study will be achieved. Be sure to provide enough detail to enable the reader can make an informed assessment of the methods being used to obtain results associated with the research problem. The methods section should be presented in the past tense.

• Study population and sampling -- where did the data come from; how robust is it; note where gaps exist or what was excluded. Note the procedures used for their selection;
• Data collection – describe the tools and methods used to collect information and identify the variables being measured; describe the methods used to obtain the data; and, note if the data was pre-existing [i.e., government data] or you gathered it yourself. If you gathered it yourself, describe what type of instrument you used and why. Note that no data set is perfect--describe any limitations in methods of gathering data.
• Data analysis -- describe the procedures for processing and analyzing the data. If appropriate, describe the specific instruments of analysis used to study each research objective, including mathematical techniques and the type of computer software used to manipulate the data.

Results The finding of your study should be written objectively and in a succinct and precise format. In quantitative studies, it is common to use graphs, tables, charts, and other non-textual elements to help the reader understand the data. Make sure that non-textual elements do not stand in isolation from the text but are being used to supplement the overall description of the results and to help clarify key points being made. Further information about how to effectively present data using charts and graphs can be found here .

• Statistical analysis -- how did you analyze the data? What were the key findings from the data? The findings should be present in a logical, sequential order. Describe but do not interpret these trends or negative results; save that for the discussion section. The results should be presented in the past tense.

Discussion Discussions should be analytic, logical, and comprehensive. The discussion should meld together your findings in relation to those identified in the literature review, and placed within the context of the theoretical framework underpinning the study. The discussion should be presented in the present tense.

• Interpretation of results -- reiterate the research problem being investigated and compare and contrast the findings with the research questions underlying the study. Did they affirm predicted outcomes or did the data refute it?
• Description of trends, comparison of groups, or relationships among variables -- describe any trends that emerged from your analysis and explain all unanticipated and statistical insignificant findings.
• Discussion of implications – what is the meaning of your results? Highlight key findings based on the overall results and note findings that you believe are important. How have the results helped fill gaps in understanding the research problem?
• Limitations -- describe any limitations or unavoidable bias in your study and, if necessary, note why these limitations did not inhibit effective interpretation of the results.

Conclusion End your study by to summarizing the topic and provide a final comment and assessment of the study.

• Summary of findings – synthesize the answers to your research questions. Do not report any statistical data here; just provide a narrative summary of the key findings and describe what was learned that you did not know before conducting the study.
• Recommendations – if appropriate to the aim of the assignment, tie key findings with policy recommendations or actions to be taken in practice.
• Future research – note the need for future research linked to your study’s limitations or to any remaining gaps in the literature that were not addressed in your study.

Black, Thomas R. Doing Quantitative Research in the Social Sciences: An Integrated Approach to Research Design, Measurement and Statistics . London: Sage, 1999; Gay,L. R. and Peter Airasain. Educational Research: Competencies for Analysis and Applications . 7th edition. Upper Saddle River, NJ: Merril Prentice Hall, 2003; Hector, Anestine. An Overview of Quantitative Research in Composition and TESOL . Department of English, Indiana University of Pennsylvania; Hopkins, Will G. “Quantitative Research Design.” Sportscience 4, 1 (2000); "A Strategy for Writing Up Research Results. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper." Department of Biology. Bates College; Nenty, H. Johnson. "Writing a Quantitative Research Thesis." International Journal of Educational Science 1 (2009): 19-32; Ouyang, Ronghua (John). Basic Inquiry of Quantitative Research . Kennesaw State University.

Strengths of Using Quantitative Methods

Quantitative researchers try to recognize and isolate specific variables contained within the study framework, seek correlation, relationships and causality, and attempt to control the environment in which the data is collected to avoid the risk of variables, other than the one being studied, accounting for the relationships identified.

Among the specific strengths of using quantitative methods to study social science research problems:

• Allows for a broader study, involving a greater number of subjects, and enhancing the generalization of the results;
• Allows for greater objectivity and accuracy of results. Generally, quantitative methods are designed to provide summaries of data that support generalizations about the phenomenon under study. In order to accomplish this, quantitative research usually involves few variables and many cases, and employs prescribed procedures to ensure validity and reliability;
• Applying well established standards means that the research can be replicated, and then analyzed and compared with similar studies;
• You can summarize vast sources of information and make comparisons across categories and over time; and,
• Personal bias can be avoided by keeping a 'distance' from participating subjects and using accepted computational techniques .

Babbie, Earl R. The Practice of Social Research . 12th ed. Belmont, CA: Wadsworth Cengage, 2010; Brians, Craig Leonard et al. Empirical Political Analysis: Quantitative and Qualitative Research Methods . 8th ed. Boston, MA: Longman, 2011; McNabb, David E. Research Methods in Public Administration and Nonprofit Management: Quantitative and Qualitative Approaches . 2nd ed. Armonk, NY: M.E. Sharpe, 2008; Singh, Kultar. Quantitative Social Research Methods . Los Angeles, CA: Sage, 2007.

Limitations of Using Quantitative Methods

Quantitative methods presume to have an objective approach to studying research problems, where data is controlled and measured, to address the accumulation of facts, and to determine the causes of behavior. As a consequence, the results of quantitative research may be statistically significant but are often humanly insignificant.

Some specific limitations associated with using quantitative methods to study research problems in the social sciences include:

• Quantitative data is more efficient and able to test hypotheses, but may miss contextual detail;
• Uses a static and rigid approach and so employs an inflexible process of discovery;
• The development of standard questions by researchers can lead to "structural bias" and false representation, where the data actually reflects the view of the researcher instead of the participating subject;
• Results provide less detail on behavior, attitudes, and motivation;
• Researcher may collect a much narrower and sometimes superficial dataset;
• Results are limited as they provide numerical descriptions rather than detailed narrative and generally provide less elaborate accounts of human perception;
• The research is often carried out in an unnatural, artificial environment so that a level of control can be applied to the exercise. This level of control might not normally be in place in the real world thus yielding "laboratory results" as opposed to "real world results"; and,
• Preset answers will not necessarily reflect how people really feel about a subject and, in some cases, might just be the closest match to the preconceived hypothesis.

Research Tip

Finding Examples of How to Apply Different Types of Research Methods

SAGE publications is a major publisher of studies about how to design and conduct research in the social and behavioral sciences. Their SAGE Research Methods Online and Cases database includes contents from books, articles, encyclopedias, handbooks, and videos covering social science research design and methods including the complete Little Green Book Series of Quantitative Applications in the Social Sciences and the Little Blue Book Series of Qualitative Research techniques. The database also includes case studies outlining the research methods used in real research projects. This is an excellent source for finding definitions of key terms and descriptions of research design and practice, techniques of data gathering, analysis, and reporting, and information about theories of research [e.g., grounded theory]. The database covers both qualitative and quantitative research methods as well as mixed methods approaches to conducting research.

SAGE Research Methods Online and Cases

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Quantitative and Qualitative Research

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What is Quantitative Research?

• What is Qualitative Research?
• Quantitative vs Qualitative
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Quantitative methodology is the dominant research framework in the social sciences. It refers to a set of strategies, techniques and assumptions used to study psychological, social and economic processes through the exploration of numeric patterns . Quantitative research gathers a range of numeric data. Some of the numeric data is intrinsically quantitative (e.g. personal income), while in other cases the numeric structure is  imposed (e.g. ‘On a scale from 1 to 10, how depressed did you feel last week?’). The collection of quantitative information allows researchers to conduct simple to extremely sophisticated statistical analyses that aggregate the data (e.g. averages, percentages), show relationships among the data (e.g. ‘Students with lower grade point averages tend to score lower on a depression scale’) or compare across aggregated data (e.g. the USA has a higher gross domestic product than Spain). Quantitative research includes methodologies such as questionnaires, structured observations or experiments and stands in contrast to qualitative research. Qualitative research involves the collection and analysis of narratives and/or open-ended observations through methodologies such as interviews, focus groups or ethnographies.

Coghlan, D., Brydon-Miller, M. (2014).  The SAGE encyclopedia of action research  (Vols. 1-2). London, : SAGE Publications Ltd doi: 10.4135/9781446294406

What is the purpose of quantitative research?

The purpose of quantitative research is to generate knowledge and create understanding about the social world. Quantitative research is used by social scientists, including communication researchers, to observe phenomena or occurrences affecting individuals. Social scientists are concerned with the study of people. Quantitative research is a way to learn about a particular group of people, known as a sample population. Using scientific inquiry, quantitative research relies on data that are observed or measured to examine questions about the sample population.

Allen, M. (2017).  The SAGE encyclopedia of communication research methods  (Vols. 1-4). Thousand Oaks, CA: SAGE Publications, Inc doi: 10.4135/9781483381411

How do I know if the study is a quantitative design?  What type of quantitative study is it?

Quantitative Research Designs: Descriptive non-experimental, Quasi-experimental or Experimental?

Studies do not always explicitly state what kind of research design is being used.  You will need to know how to decipher which design type is used.  The following video will help you determine the quantitative design type.

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Review of Related Literature: Format, Example, & How to Make RRL

A review of related literature is a separate paper or a part of an article that collects and synthesizes discussion on a topic. Its purpose is to show the current state of research on the issue and highlight gaps in existing knowledge. A literature review can be included in a research paper or scholarly article, typically following the introduction and before the research methods section.

This article will clarify the definition, significance, and structure of a review of related literature. You’ll also learn how to organize your literature review and discover ideas for an RRL in different subjects.

🔤 What Is RRL?

• ❗ Significance of Literature Review
• 🔎 How to Search for Literature
• 🧩 Literature Review Structure
• 📋 Format of RRL — APA, MLA, & Others
• ✍️ How to Write an RRL
• 📚 Examples of RRL

🔗 References

A review of related literature (RRL) is a part of the research report that examines significant studies, theories, and concepts published in scholarly sources on a particular topic. An RRL includes 3 main components:

• A short overview and critique of the previous research.
• Similarities and differences between past studies and the current one.
• An explanation of the theoretical frameworks underpinning the research.

❗ Significance of Review of Related Literature

Although the goal of a review of related literature differs depending on the discipline and its intended use, its significance cannot be overstated. Here are some examples of how a review might be beneficial:

• It helps determine knowledge gaps .
• It saves from duplicating research that has already been conducted.
• It provides an overview of various research areas within the discipline.
• It demonstrates the researcher’s familiarity with the topic.

🔎 How to Perform a Literature Search

Including a description of your search strategy in the literature review section can significantly increase your grade. You can search sources with the following steps:

🧩 Literature Review Structure Example

The majority of literature reviews follow a standard introduction-body-conclusion structure. Let’s look at the RRL structure in detail.

Introduction of Review of Related Literature: Sample

An introduction should clarify the study topic and the depth of the information to be delivered. It should also explain the types of sources used. If your lit. review is part of a larger research proposal or project, you can combine its introductory paragraph with the introduction of your paper.

Here is a sample introduction to an RRL about cyberbullying:

Bullying has troubled people since the beginning of time. However, with modern technological advancements, especially social media, bullying has evolved into cyberbullying. As a result, nowadays, teenagers and adults cannot flee their bullies, which makes them feel lonely and helpless. This literature review will examine recent studies on cyberbullying.

Sample Review of Related Literature Thesis

A thesis statement should include the central idea of your literature review and the primary supporting elements you discovered in the literature. Thesis statements are typically put at the end of the introductory paragraph.

Look at a sample thesis of a review of related literature:

This literature review shows that scholars have recently covered the issues of bullies’ motivation, the impact of bullying on victims and aggressors, common cyberbullying techniques, and victims’ coping strategies. However, there is still no agreement on the best practices to address cyberbullying.

Literature Review Body Paragraph Example

The main body of a literature review should provide an overview of the existing research on the issue. Body paragraphs should not just summarize each source but analyze them. You can organize your paragraphs with these 3 elements:

• Claim . Start with a topic sentence linked to your literature review purpose.
• Evidence . Cite relevant information from your chosen sources.
• Discussion . Explain how the cited data supports your claim.

Here’s a literature review body paragraph example:

Scholars have examined the link between the aggressor and the victim. Beran et al. (2007) state that students bullied online often become cyberbullies themselves. Faucher et al. (2014) confirm this with their findings: they discovered that male and female students began engaging in cyberbullying after being subject to bullying. Hence, one can conclude that being a victim of bullying increases one’s likelihood of becoming a cyberbully.

Review of Related Literature: Conclusion

A conclusion presents a general consensus on the topic. Depending on your literature review purpose, it might include the following:

• Introduction to further research . If you write a literature review as part of a larger research project, you can present your research question in your conclusion .
• Overview of theories . You can summarize critical theories and concepts to help your reader understand the topic better.
• Discussion of the gap . If you identified a research gap in the reviewed literature, your conclusion could explain why that gap is significant.

Check out a conclusion example that discusses a research gap:

There is extensive research into bullies’ motivation, the consequences of bullying for victims and aggressors, strategies for bullying, and coping with it. Yet, scholars still have not reached a consensus on what to consider the best practices to combat cyberbullying. This question is of great importance because of the significant adverse effects of cyberbullying on victims and bullies.

📋 Format of RRL — APA, MLA, & Others

In this section, we will discuss how to format an RRL according to the most common citation styles: APA, Chicago, MLA, and Harvard.

Writing a literature review using the APA7 style requires the following text formatting:

• When using APA in-text citations , include the author’s last name and the year of publication in parentheses.
• For direct quotations , you must also add the page number. If you use sources without page numbers, such as websites or e-books, include a paragraph number instead.
• When referring to the author’s name in a sentence , you do not need to repeat it at the end of the sentence. Instead, include the year of publication inside the parentheses after their name.
• The reference list should be included at the end of your literature review. It is always alphabetized by the last name of the author (from A to Z), and the lines are indented one-half inch from the left margin of your paper. Do not forget to invert authors’ names (the last name should come first) and include the full titles of journals instead of their abbreviations. If you use an online source, add its URL.

The RRL format in the Chicago style is as follows:

• Author-date . You place your citations in brackets within the text, indicating the name of the author and the year of publication.
• Notes and bibliography . You place your citations in numbered footnotes or endnotes to connect the citation back to the source in the bibliography.
• The reference list, or bibliography , in Chicago style, is at the end of a literature review. The sources are arranged alphabetically and single-spaced. Each bibliography entry begins with the author’s name and the source’s title, followed by publication information, such as the city of publication, the publisher, and the year of publication.

Writing a literature review using the MLA style requires the following text formatting:

• In the MLA format, you can cite a source in the text by indicating the author’s last name and the page number in parentheses at the end of the citation. If the cited information takes several pages, you need to include all the page numbers.
• The reference list in MLA style is titled “ Works Cited .” In this section, all sources used in the paper should be listed in alphabetical order. Each entry should contain the author, title of the source, title of the journal or a larger volume, other contributors, version, number, publisher, and publication date.

The Harvard style requires you to use the following text formatting for your RRL:

• In-text citations in the Harvard style include the author’s last name and the year of publication. If you are using a direct quote in your literature review, you need to add the page number as well.
• Arrange your list of references alphabetically. Each entry should contain the author’s last name, their initials, the year of publication, the title of the source, and other publication information, like the journal title and issue number or the publisher.

✍️ How to Write Review of Related Literature – Sample

Literature reviews can be organized in many ways depending on what you want to achieve with them. In this section, we will look at 3 examples of how you can write your RRL.

Thematic Literature Review

A thematic literature review is arranged around central themes or issues discussed in the sources. If you have identified some recurring themes in the literature, you can divide your RRL into sections that address various aspects of the topic. For example, if you examine studies on e-learning, you can distinguish such themes as the cost-effectiveness of online learning, the technologies used, and its effectiveness compared to traditional education.

Chronological Literature Review

A chronological literature review is a way to track the development of the topic over time. If you use this method, avoid merely listing and summarizing sources in chronological order. Instead, try to analyze the trends, turning moments, and critical debates that have shaped the field’s path. Also, you can give your interpretation of how and why specific advances occurred.

Methodological Literature Review

A methodological literature review differs from the preceding ones in that it usually doesn’t focus on the sources’ content. Instead, it is concerned with the research methods . So, if your references come from several disciplines or fields employing various research techniques, you can compare the findings and conclusions of different methodologies, for instance:

• empirical vs. theoretical studies;
• qualitative vs. quantitative research.

📚 Examples of Review of Related Literature and Studies

We have prepared a short example of RRL on climate change for you to see how everything works in practice!

Climate change is one of the most important issues nowadays. Based on a variety of facts, it is now clearer than ever that humans are altering the Earth's climate. The atmosphere and oceans have warmed, causing sea level rise, a significant loss of Arctic ice, and other climate-related changes. This literature review provides a thorough summary of research on climate change, focusing on climate change fingerprints and evidence of human influence on the Earth's climate system.

Physical Mechanisms and Evidence of Human Influence

Scientists are convinced that climate change is directly influenced by the emission of greenhouse gases. They have carefully analyzed various climate data and evidence, concluding that the majority of the observed global warming over the past 50 years cannot be explained by natural factors alone. Instead, there is compelling evidence pointing to a significant contribution of human activities, primarily the emission of greenhouse gases (Walker, 2014). For example, based on simple physics calculations, doubled carbon dioxide concentration in the atmosphere can lead to a global temperature increase of approximately 1 degree Celsius. (Elderfield, 2022). In order to determine the human influence on climate, scientists still have to analyze a lot of natural changes that affect temperature, precipitation, and other components of climate on timeframes ranging from days to decades and beyond.

Fingerprinting Climate Change

Fingerprinting climate change is a useful tool to identify the causes of global warming because different factors leave unique marks on climate records. This is evident when scientists look beyond overall temperature changes and examine how warming is distributed geographically and over time (Watson, 2022). By investigating these climate patterns, scientists can obtain a more complex understanding of the connections between natural climate variability and climate variability caused by human activity.

Modeling Climate Change and Feedback

To accurately predict the consequences of feedback mechanisms, the rate of warming, and regional climate change, scientists can employ sophisticated mathematical models of the atmosphere, ocean, land, and ice (the cryosphere). These models are grounded in well-established physical laws and incorporate the latest scientific understanding of climate-related processes (Shuckburgh, 2013). Although different climate models produce slightly varying projections for future warming, they all will agree that feedback mechanisms play a significant role in amplifying the initial warming caused by greenhouse gas emissions. (Meehl, 2019).

In conclusion, the literature on global warming indicates that there are well-understood physical processes that link variations in greenhouse gas concentrations to climate change. In addition, it covers the scientific proof that the rates of these gases in the atmosphere have increased and continue to rise fast. According to the sources, the majority of this recent change is almost definitely caused by greenhouse gas emissions produced by human activities. Citizens and governments can alter their energy production methods and consumption patterns to reduce greenhouse gas emissions and, thus, the magnitude of climate change. By acting now, society can prevent the worst consequences of climate change and build a more resilient and sustainable future for generations to come.

Have you ever struggled with finding the topic for an RRL in different subjects? Read the following paragraphs to get some ideas!

Nursing Literature Review Example

Many topics in the nursing field require research. For example, you can write a review of literature related to dengue fever . Give a general overview of dengue virus infections, including its clinical symptoms, diagnosis, prevention, and therapy.

Another good idea is to review related literature and studies about teenage pregnancy . This review can describe the effectiveness of specific programs for adolescent mothers and their children and summarize recommendations for preventing early pregnancy.

📝 Check out some more valuable examples below:

• Hospital Readmissions: Literature Review .
• Literature Review: Lower Sepsis Mortality Rates .
• Breast Cancer: Literature Review .
• Sexually Transmitted Diseases: Literature Review .
• PICO for Pressure Ulcers: Literature Review .
• COVID-19 Spread Prevention: Literature Review .
• Chronic Obstructive Pulmonary Disease: Literature Review .
• Hypertension Treatment Adherence: Literature Review .
• Neonatal Sepsis Prevention: Literature Review .
• Healthcare-Associated Infections: Literature Review .
• Understaffing in Nursing: Literature Review .

Psychology Literature Review Example

If you look for an RRL topic in psychology , you can write a review of related literature about stress . Summarize scientific evidence about stress stages, side effects, types, or reduction strategies. Or you can write a review of related literature about computer game addiction . In this case, you may concentrate on the neural mechanisms underlying the internet gaming disorder, compare it to other addictions, or evaluate treatment strategies.

A review of related literature about cyberbullying is another interesting option. You can highlight the impact of cyberbullying on undergraduate students’ academic, social, and emotional development.

📝 Look at the examples that we have prepared for you to come up with some more ideas:

• Mindfulness in Counseling: A Literature Review .
• Team-Building Across Cultures: Literature Review .
• Anxiety and Decision Making: Literature Review .
• Literature Review on Depression .
• Literature Review on Narcissism .
• Effects of Depression Among Adolescents .
• Causes and Effects of Anxiety in Children .

Literature Review — Sociology Example

Sociological research poses critical questions about social structures and phenomena. For example, you can write a review of related literature about child labor , exploring cultural beliefs and social norms that normalize the exploitation of children. Or you can create a review of related literature about social media . It can investigate the impact of social media on relationships between adolescents or the role of social networks on immigrants’ acculturation .

📝 You can find some more ideas below!

• Single Mothers’ Experiences of Relationships with Their Adolescent Sons .
• Teachers and Students’ Gender-Based Interactions .
• Gender Identity: Biological Perspective and Social Cognitive Theory .
• Gender: Culturally-Prescribed Role or Biological Sex .
• The Influence of Opioid Misuse on Academic Achievement of Veteran Students .
• The Importance of Ethics in Research .
• The Role of Family and Social Network Support in Mental Health .

Education Literature Review Example

For your education studies , you can write a review of related literature about academic performance to determine factors that affect student achievement and highlight research gaps. One more idea is to create a review of related literature on study habits , considering their role in the student’s life and academic outcomes.

You can also evaluate a computerized grading system in a review of related literature to single out its advantages and barriers to implementation. Or you can complete a review of related literature on instructional materials to identify their most common types and effects on student achievement.

📝 Find some inspiration in the examples below:

• Literature Review on Online Learning Challenges From COVID-19 .
• Education, Leadership, and Management: Literature Review .
• Literature Review: Standardized Testing Bias .
• Bullying of Disabled Children in School .
• Interventions and Letter & Sound Recognition: A Literature Review .
• Social-Emotional Skills Program for Preschoolers .
• Effectiveness of Educational Leadership Management Skills .

Business Research Literature Review

If you’re a business student, you can focus on customer satisfaction in your review of related literature. Discuss specific customer satisfaction features and how it is affected by service quality and prices. You can also create a theoretical literature review about consumer buying behavior to evaluate theories that have significantly contributed to understanding how consumers make purchasing decisions.

📝 Look at the examples to get more exciting ideas:

• Leadership and Communication: Literature Review .
• Human Resource Development: Literature Review .
• Project Management. Literature Review .
• Strategic HRM: A Literature Review .
• Customer Relationship Management: Literature Review .
• Literature Review on International Financial Reporting Standards .
• Cultures of Management: Literature Review .

To conclude, a review of related literature is a significant genre of scholarly works that can be applied in various disciplines and for multiple goals. The sources examined in an RRL provide theoretical frameworks for future studies and help create original research questions and hypotheses.

When you finish your outstanding literature review, don’t forget to check whether it sounds logical and coherent. Our text-to-speech tool can help you with that!

• Literature Reviews | University of North Carolina at Chapel Hill
• Writing a Literature Review | Purdue Online Writing Lab
• Learn How to Write a Review of Literature | University of Wisconsin-Madison
• The Literature Review: A Few Tips on Conducting It | University of Toronto
• Writing a Literature Review | UC San Diego
• Conduct a Literature Review | The University of Arizona
• Methods for Literature Reviews | National Library of Medicine
• Literature Reviews: 5. Write the Review | Georgia State University

How to Write an Animal Testing Essay: Tips for Argumentative & Persuasive Papers

Descriptive essay topics: examples, outline, & more.

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How to structure quantitative research questions

There is no "one best way" to structure a quantitative research question. However, to create a well-structured quantitative research question, we recommend an approach that is based on four steps : (1) Choosing the type of quantitative research question you are trying to create (i.e., descriptive, comparative or relationship-based); (2) Identifying the different types of variables you are trying to measure, manipulate and/or control, as well as any groups you may be interested in; (3) Selecting the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved; and (4) Writing out the problem or issues you are trying to address in the form of a complete research question. In this article, we discuss each of these four steps , as well as providing examples for the three types of quantitative research question you may want to create: descriptive , comparative and relationship-based research questions .

• STEP ONE: Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create
• STEP TWO: Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in
• STEP THREE: Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved
• STEP FOUR: Write out the problem or issues you are trying to address in the form of a complete research question

STEP ONE Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create

The type of quantitative research question that you use in your dissertation (i.e., descriptive , comparative and/or relationship-based ) needs to be reflected in the way that you write out the research question; that is, the word choice and phrasing that you use when constructing a research question tells the reader whether it is a descriptive, comparative or relationship-based research question. Therefore, in order to know how to structure your quantitative research question, you need to start by selecting the type of quantitative research question you are trying to create: descriptive, comparative and/or relationship-based.

STEP TWO Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in

Whether you are trying to create a descriptive, comparative or relationship-based research question, you will need to identify the different types of variable that you are trying to measure , manipulate and/or control . If you are unfamiliar with the different types of variable that may be part of your study, the article, Types of variable , should get you up to speed. It explains the two main types of variables: categorical variables (i.e., nominal , dichotomous and ordinal variables) and continuous variables (i.e., interval and ratio variables). It also explains the difference between independent and dependent variables , which you need to understand to create quantitative research questions.

To provide a brief explanation; a variable is not only something that you measure , but also something that you can manipulate and control for. In most undergraduate and master's level dissertations, you are only likely to measure and manipulate variables. You are unlikely to carry out research that requires you to control for variables, although some supervisors will expect this additional level of complexity. If you plan to only create descriptive research questions , you may simply have a number of dependent variables that you need to measure. However, where you plan to create comparative and/or relationship-based research questions , you will deal with both dependent and independent variables . An independent variable (sometimes called an experimental or predictor variable ) is a variable that is being manipulated in an experiment in order to observe the effect this has on a dependent variable (sometimes called an outcome variable ). For example, if we were interested in investigating the relationship between gender and attitudes towards music piracy amongst adolescents , the independent variable would be gender and the dependent variable attitudes towards music piracy . This example also highlights the need to identify the group(s) you are interested in. In this example, the group of interest are adolescents .

Once you identifying the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in, it is possible to start thinking about the way that the three types of quantitative research question can be structured . This is discussed next.

STEP THREE Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved

The structure of the three types of quantitative research question differs, reflecting the goals of the question, the types of variables, and the number of variables and groups involved. By structure , we mean the components of a research question (i.e., the types of variables, groups of interest), the number of these different components (i.e., how many variables and groups are being investigated), and the order that these should be presented (e.g., independent variables before dependent variables). The appropriate structure for each of these quantitative research questions is set out below:

Structure of descriptive research questions

• Structure of comparative research questions
• Structure of relationship-based research questions

There are six steps required to construct a descriptive research question: (1) choose your starting phrase; (2) identify and name the dependent variable; (3) identify the group(s) you are interested in; (4) decide whether dependent variable or group(s) should be included first, last or in two parts; (5) include any words that provide greater context to your question; and (6) write out the descriptive research question. Each of these steps is discussed in turn:

Choose your starting phrase

Identify and name the dependent variable

Identify the group(s) you are interested in

Decide whether the dependent variable or group(s) should be included first, last or in two parts

Include any words that provide greater context to your question

Write out the descriptive research question

FIRST Choose your starting phrase

You can start descriptive research questions with any of the following phrases:

How many? How often? How frequently? How much? What percentage? What proportion? To what extent? What is? What are?

Some of these starting phrases are highlighted in blue text in the examples below:

How many calories do American men and women consume per day?

How often do British university students use Facebook each week?

What are the most important factors that influence the career choices of Australian university students?

What proportion of British male and female university students use the top 5 social networks?

What percentage of American men and women exceed their daily calorific allowance?

SECOND Identify and name the dependent variable

All descriptive research questions have a dependent variable. You need to identify what this is. However, how the dependent variable is written out in a research question and what you call it are often two different things. In the examples below, we have illustrated the name of the dependent variable and highlighted how it would be written out in the blue text .

The first two examples highlight that while the name of the dependent variable is the same, namely daily calorific intake , the way that this dependent variable is written out differs in each case.

THIRD Identify the group(s) you are interested in

All descriptive research questions have at least one group , but can have multiple groups . You need to identify this group(s). In the examples below, we have identified the group(s) in the green text .

What are the most important factors that influence the career choices of Australian university students ?

The examples illustrate the difference between the use of a single group (e.g., British university students ) and multiple groups (e.g., American men and women ).

FOURTH Decide whether the dependent variable or group(s) should be included first, last or in two parts

Sometimes it makes more sense for the dependent variable to appear before the group(s) you are interested in, but sometimes it is the opposite way around. The following examples illustrate this, with the group(s) in green text and the dependent variable in blue text :

Group 1st; dependent variable 2nd:

How often do British university students use Facebook each week ?

Dependent variable 1st; group 2nd:

Sometimes, the dependent variable needs to be broken into two parts around the group(s) you are interested in so that the research question flows. Again, the group(s) are in green text and the dependent variable is in blue text :

How many calories do American men and women consume per day ?

Of course, you could choose to restructure the question above so that you do not have to split the dependent variable into two parts. For example:

How many calories are consumed per day by American men and women ?

When deciding whether the dependent variable or group(s) should be included first or last, and whether the dependent variable should be broken into two parts, the main thing you need to think about is flow : Does the question flow? Is it easy to read?

FIFTH Include any words that provide greater context to your question

Sometimes the name of the dependent variable provides all the explanation we need to know what we are trying to measure. Take the following examples:

In the first example, the dependent variable is daily calorific intake (i.e., calories consumed per day). Clearly, this descriptive research question is asking us to measure the number of calories American men and women consume per day. In the second example, the dependent variable is Facebook usage per week. Again, the name of this dependent variable makes it easy for us to understand that we are trying to measure the often (i.e., how frequently; e.g., 16 times per week) British university students use Facebook.

However, sometimes a descriptive research question is not simply interested in measuring the dependent variable in its entirety, but a particular component of the dependent variable. Take the following examples in red text :

In the first example, the research question is not simply interested in the daily calorific intake of American men and women, but what percentage of these American men and women exceeded their daily calorific allowance. So the dependent variable is still daily calorific intake, but the research question aims to understand a particular component of that dependent variable (i.e., the percentage of American men and women exceeding the recommend daily calorific allowance). In the second example, the research question is not only interested in what the factors influencing career choices are, but which of these factors are the most important.

Therefore, when you think about constructing your descriptive research question, make sure you have included any words that provide greater context to your question.

SIXTH Write out the descriptive research question

Once you have these details ? (1) the starting phrase, (2) the name of the dependent variable, (3) the name of the group(s) you are interested in, and (4) any potential joining words ? you can write out the descriptive research question in full. The example descriptive research questions discussed above are written out in full below:

In the section that follows, the structure of comparative research questions is discussed.

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How to Write Quantitative Research Questions: Types With Examples

For research to be effective, it becomes crucial to properly formulate the quantitative research questions in a correct way. Otherwise, you will not get the answers you were looking for.

Has it ever happened that you conducted a quantitative research study and found out the results you were expecting are quite different from the actual results?

This could happen due to many factors like the unpredictable nature of respondents, errors in calculation, research bias, etc. However, your quantitative research usually does not provide reliable results when questions are not written correctly.

We get it! Structuring the quantitative research questions can be a difficult task.

Hence, in this blog, we will share a few bits of advice on how to write good quantitative research questions. We will also look at different types of quantitative research questions along with their examples.

Let’s start:

How to Write Quantitative Research Questions?

When you want to obtain actionable insight into the trends and patterns of the research topic to make sense of it, quantitative research questions are your best bet.

Being objective in nature, these questions provide you with detailed information about the research topic and help in collecting quantifiable data that can be easily analyzed. This data can be generalized to the entire population and help make data-driven and sound decisions.

Respondents find it easier to answer quantitative survey questions than qualitative questions . At the same time, researchers can also analyze them quickly using various statistical models.

However, when it comes to writing the quantitative research questions, one can get a little overwhelmed as the entire study depends on the types of questions used.

There is no “one good way” to prepare these questions. However, to design well-structured quantitative research questions, you can follow the 4-steps approach given below:

1. Select the Type of Quantitative Question

The first step is to determine which type of quantitative question you want to add to your study. There are three types of quantitative questions:

• Descriptive
• Comparative 
• Relationship-based

This will help you choose the correct words and phrases while constructing the question. At the same time, it will also assist readers in understanding the question correctly.

2. Identify the Type of Variable

The second step involves identifying the type of variable you are trying to measure, manipulate, or control. Basically, there are two types of variables:

• Independent variable (a variable that is being manipulated)
• Dependent variable (outcome variable)

If you plan to use descriptive research questions, you have to deal with a number of dependent variables. However, where you plan to create comparative or relationship research questions, you will deal with both dependent and independent variables.

3. Select the Suitable Structure

The next step is determining the structure of the research question. It involves:

• Identifying the components of the question. It involves the type of dependent or independent variable and a group of interest (the group from which the researcher tries to conclude the population).
• The number of different components used. Like, as to how many variables and groups are being examined.
• Order in which these are presented. For example, the independent variable before the dependent variable or vice versa.

4. Draft the Complete Research Question

The last step involves identifying the problem or issue that you are trying to address in the form of complete quantitative survey questions. Also, make sure to build an exhaustive list of response options to make sure your respondents select the correct response. If you miss adding important answer options, then the ones chosen by respondents may not be entirely true.

Types of Quantitative Research Questions With Examples

Quantitative research questions are generally used to answer the “who” and “what” of the research topic. For quantitative research to be effective, it is crucial that the respondents are able to answer your questions concisely and precisely. With that in mind, let’s look in greater detail at the three types of formats you can use when preparing quantitative market research questions.

1. Descriptive

Descriptive research questions are used to collect participants’ opinions about the variable that you want to quantify. It is the most effortless way to measure the particular variable (single or multiple variables) you are interested in on a large scale. Usually, descriptive research questions begin with “ how much,” “how often,” “what percentage,” “what proportion,” etc.

Examples of descriptive research questions include:

2. Comparative

Comparative research questions help you identify the difference between two or more groups based on one or more variables. In general, a comparative research question is used to quantify one variable; however, you can use two or more variables depending on your market research objectives.

Comparative research questions examples include:

3. Relationship-based

Relationship research questions are used to identify trends, causal relationships, or associations between two or more variables. It is not vital to distinguish between causal relationships, trends, or associations while using these types of questions. These questions begin with “What is the relationship” between independent and dependent variables, amongst or between two or more groups.

Relationship-based quantitative questions examples include:

Ready to Write Your Quantitative Research Questions?

So, there you have it. It was all about quantitative research question types and their examples. By now, you must have figured out a way to write quantitative research questions for your survey to collect actionable customer feedback.

Now, the only thing you need is a good survey maker tool, like ProProfs Survey Maker, that will glide your process of designing and conducting your surveys . You also get access to various survey question types, both qualitative and quantitative, that you can add to any kind of survey along with professionally-designed survey templates .

About the author

Emma David is a seasoned market research professional with 8+ years of experience. Having kick-started her journey in research, she has developed rich expertise in employee engagement, survey creation and administration, and data management. Emma believes in the power of data to shape business performance positively. She continues to help brands and businesses make strategic decisions and improve their market standing through her understanding of research methodologies.

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Letter: PMA expansion a study in thoughtfulness

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I am writing in defense of the Portland Museum of Art expansion plan. As a trustee, I have witnessed the extensive due diligence performed by the museum to reach this point. Thorough feasibility studies and many months of research and input from a broad spectrum of the Portland community have helped us understand how best to represent the needs of our diverse population.

This decision to replace the existing Free Street structure was not made lightly. The PMA is a champion of architecture, and has a collection of historically significant buildings that are lovingly maintained, including the Homer Studio and L.D.M. Seat Memorial Galleries, both designed by John Calvin Stevens. In the new final design, the only change to the Payson building elevation is that the entrances to the “campus” will be on Free Street and High Street. The new, sustainable building, to be designed by LEVER Architects, will be built largely from mass timber, not all glass.

The PMA’s mission statement is “art for all.” Free admission for people under 21 all of the time, Free Fridays, numerous family and school programs, and collection exhibitions that examine our past through a more inclusive lens are just some of the ways this is being addressed.

The economic impacts of the project will help revitalize Congress Square, enhance the community, and Portland’s Comprehensive Plan 2030 will benefit. I truly believe that over time the new addition will become a beloved structure, with its open design welcoming to all.

Tina Petra Portland

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