writing a quantitative research thesis

• USC Libraries
• Research Guides

Organizing Your Social Sciences Research Paper

• Quantitative Methods
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
• Research Process Video Series
• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
• Writing Concisely
• Avoiding Plagiarism
• Footnotes or Endnotes?
• Further Readings
• Generative AI and Writing
• USC Libraries Tutorials and Other Guides
• Bibliography

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

• << Previous: Qualitative Methods
• Next: Insiderness >>
• Last Updated: Aug 30, 2024 10:02 AM
• URL: https://libguides.usc.edu/writingguide

How To Write A Dissertation Or Thesis

8 straightforward steps to craft an a-grade dissertation.

By: Derek Jansen (MBA) Expert Reviewed By: Dr Eunice Rautenbach | June 2020

Writing a dissertation or thesis is not a simple task. It takes time, energy and a lot of will power to get you across the finish line. It’s not easy – but it doesn’t necessarily need to be a painful process. If you understand the big-picture process of how to write a dissertation or thesis, your research journey will be a lot smoother.  

In this post, I’m going to outline the big-picture process of how to write a high-quality dissertation or thesis, without losing your mind along the way. If you’re just starting your research, this post is perfect for you. Alternatively, if you’ve already submitted your proposal, this article which covers how to structure a dissertation might be more helpful.

How To Write A Dissertation: 8 Steps

• Clearly understand what a dissertation (or thesis) is
• Find a unique and valuable research topic
• Craft a convincing research proposal
• Write up a strong introduction chapter
• Review the existing literature and compile a literature review
• Design a rigorous research strategy and undertake your own research
• Present the findings of your research
• Draw a conclusion and discuss the implications

Step 1: Understand exactly what a dissertation is

This probably sounds like a no-brainer, but all too often, students come to us for help with their research and the underlying issue is that they don’t fully understand what a dissertation (or thesis) actually is.

So, what is a dissertation?

At its simplest, a dissertation or thesis is a formal piece of research , reflecting the standard research process . But what is the standard research process, you ask? The research process involves 4 key steps:

• Ask a very specific, well-articulated question (s) (your research topic)
• See what other researchers have said about it (if they’ve already answered it)
• If they haven’t answered it adequately, undertake your own data collection and analysis in a scientifically rigorous fashion
• Answer your original question(s), based on your analysis findings

In short, the research process is simply about asking and answering questions in a systematic fashion . This probably sounds pretty obvious, but people often think they’ve done “research”, when in fact what they have done is:

• Started with a vague, poorly articulated question
• Not taken the time to see what research has already been done regarding the question
• Collected data and opinions that support their gut and undertaken a flimsy analysis
• Drawn a shaky conclusion, based on that analysis

If you want to see the perfect example of this in action, look out for the next Facebook post where someone claims they’ve done “research”… All too often, people consider reading a few blog posts to constitute research. Its no surprise then that what they end up with is an opinion piece, not research. Okay, okay – I’ll climb off my soapbox now.

The key takeaway here is that a dissertation (or thesis) is a formal piece of research, reflecting the research process. It’s not an opinion piece , nor a place to push your agenda or try to convince someone of your position. Writing a good dissertation involves asking a question and taking a systematic, rigorous approach to answering it.

If you understand this and are comfortable leaving your opinions or preconceived ideas at the door, you’re already off to a good start!

Step 2: Find a unique, valuable research topic

As we saw, the first step of the research process is to ask a specific, well-articulated question. In other words, you need to find a research topic that asks a specific question or set of questions (these are called research questions ). Sounds easy enough, right? All you’ve got to do is identify a question or two and you’ve got a winning research topic. Well, not quite…

A good dissertation or thesis topic has a few important attributes. Specifically, a solid research topic should be:

Let’s take a closer look at these:

Attribute #1: Clear

Your research topic needs to be crystal clear about what you’re planning to research, what you want to know, and within what context. There shouldn’t be any ambiguity or vagueness about what you’ll research.

Here’s an example of a clearly articulated research topic:

An analysis of consumer-based factors influencing organisational trust in British low-cost online equity brokerage firms.

As you can see in the example, its crystal clear what will be analysed (factors impacting organisational trust), amongst who (consumers) and in what context (British low-cost equity brokerage firms, based online).

Need a helping hand?

Attribute #2:   Unique

Your research should be asking a question(s) that hasn’t been asked before, or that hasn’t been asked in a specific context (for example, in a specific country or industry).

For example, sticking organisational trust topic above, it’s quite likely that organisational trust factors in the UK have been investigated before, but the context (online low-cost equity brokerages) could make this research unique. Therefore, the context makes this research original.

One caveat when using context as the basis for originality – you need to have a good reason to suspect that your findings in this context might be different from the existing research – otherwise, there’s no reason to warrant researching it.

Attribute #3: Important

Simply asking a unique or original question is not enough – the question needs to create value. In other words, successfully answering your research questions should provide some value to the field of research or the industry. You can’t research something just to satisfy your curiosity. It needs to make some form of contribution either to research or industry.

For example, researching the factors influencing consumer trust would create value by enabling businesses to tailor their operations and marketing to leverage factors that promote trust. In other words, it would have a clear benefit to industry.

So, how do you go about finding a unique and valuable research topic? We explain that in detail in this video post – How To Find A Research Topic . Yeah, we’ve got you covered 😊

Step 3: Write a convincing research proposal

Once you’ve pinned down a high-quality research topic, the next step is to convince your university to let you research it. No matter how awesome you think your topic is, it still needs to get the rubber stamp before you can move forward with your research. The research proposal is the tool you’ll use for this job.

So, what’s in a research proposal?

The main “job” of a research proposal is to convince your university, advisor or committee that your research topic is worthy of approval. But convince them of what? Well, this varies from university to university, but generally, they want to see that:

• You have a clearly articulated, unique and important topic (this might sound familiar…)
• You’ve done some initial reading of the existing literature relevant to your topic (i.e. a literature review)
• You have a provisional plan in terms of how you will collect data and analyse it (i.e. a methodology)

At the proposal stage, it’s (generally) not expected that you’ve extensively reviewed the existing literature , but you will need to show that you’ve done enough reading to identify a clear gap for original (unique) research. Similarly, they generally don’t expect that you have a rock-solid research methodology mapped out, but you should have an idea of whether you’ll be undertaking qualitative or quantitative analysis , and how you’ll collect your data (we’ll discuss this in more detail later).

Long story short – don’t stress about having every detail of your research meticulously thought out at the proposal stage – this will develop as you progress through your research. However, you do need to show that you’ve “done your homework” and that your research is worthy of approval .

So, how do you go about crafting a high-quality, convincing proposal? We cover that in detail in this video post – How To Write A Top-Class Research Proposal . We’ve also got a video walkthrough of two proposal examples here .

Step 4: Craft a strong introduction chapter

Once your proposal’s been approved, its time to get writing your actual dissertation or thesis! The good news is that if you put the time into crafting a high-quality proposal, you’ve already got a head start on your first three chapters – introduction, literature review and methodology – as you can use your proposal as the basis for these.

Handy sidenote – our free dissertation & thesis template is a great way to speed up your dissertation writing journey.

What’s the introduction chapter all about?

The purpose of the introduction chapter is to set the scene for your research (dare I say, to introduce it…) so that the reader understands what you’ll be researching and why it’s important. In other words, it covers the same ground as the research proposal in that it justifies your research topic.

What goes into the introduction chapter?

This can vary slightly between universities and degrees, but generally, the introduction chapter will include the following:

• A brief background to the study, explaining the overall area of research
• A problem statement , explaining what the problem is with the current state of research (in other words, where the knowledge gap exists)
• Your research questions – in other words, the specific questions your study will seek to answer (based on the knowledge gap)
• The significance of your study – in other words, why it’s important and how its findings will be useful in the world

As you can see, this all about explaining the “what” and the “why” of your research (as opposed to the “how”). So, your introduction chapter is basically the salesman of your study, “selling” your research to the first-time reader and (hopefully) getting them interested to read more.

How do I write the introduction chapter, you ask? We cover that in detail in this post .

Step 5: Undertake an in-depth literature review

As I mentioned earlier, you’ll need to do some initial review of the literature in Steps 2 and 3 to find your research gap and craft a convincing research proposal – but that’s just scratching the surface. Once you reach the literature review stage of your dissertation or thesis, you need to dig a lot deeper into the existing research and write up a comprehensive literature review chapter.

What’s the literature review all about?

There are two main stages in the literature review process:

Literature Review Step 1: Reading up

The first stage is for you to deep dive into the existing literature (journal articles, textbook chapters, industry reports, etc) to gain an in-depth understanding of the current state of research regarding your topic. While you don’t need to read every single article, you do need to ensure that you cover all literature that is related to your core research questions, and create a comprehensive catalogue of that literature , which you’ll use in the next step.

Reading and digesting all the relevant literature is a time consuming and intellectually demanding process. Many students underestimate just how much work goes into this step, so make sure that you allocate a good amount of time for this when planning out your research. Thankfully, there are ways to fast track the process – be sure to check out this article covering how to read journal articles quickly .

Literature Review Step 2: Writing up

Once you’ve worked through the literature and digested it all, you’ll need to write up your literature review chapter. Many students make the mistake of thinking that the literature review chapter is simply a summary of what other researchers have said. While this is partly true, a literature review is much more than just a summary. To pull off a good literature review chapter, you’ll need to achieve at least 3 things:

• You need to synthesise the existing research , not just summarise it. In other words, you need to show how different pieces of theory fit together, what’s agreed on by researchers, what’s not.
• You need to highlight a research gap that your research is going to fill. In other words, you’ve got to outline the problem so that your research topic can provide a solution.
• You need to use the existing research to inform your methodology and approach to your own research design. For example, you might use questions or Likert scales from previous studies in your your own survey design .

As you can see, a good literature review is more than just a summary of the published research. It’s the foundation on which your own research is built, so it deserves a lot of love and attention. Take the time to craft a comprehensive literature review with a suitable structure .

But, how do I actually write the literature review chapter, you ask? We cover that in detail in this video post .

Step 6: Carry out your own research

Once you’ve completed your literature review and have a sound understanding of the existing research, its time to develop your own research (finally!). You’ll design this research specifically so that you can find the answers to your unique research question.

There are two steps here – designing your research strategy and executing on it:

1 – Design your research strategy

The first step is to design your research strategy and craft a methodology chapter . I won’t get into the technicalities of the methodology chapter here, but in simple terms, this chapter is about explaining the “how” of your research. If you recall, the introduction and literature review chapters discussed the “what” and the “why”, so it makes sense that the next point to cover is the “how” –that’s what the methodology chapter is all about.

In this section, you’ll need to make firm decisions about your research design. This includes things like:

• Your research philosophy (e.g. positivism or interpretivism )
• Your overall methodology (e.g. qualitative , quantitative or mixed methods)
• Your data collection strategy (e.g. interviews , focus groups, surveys)
• Your data analysis strategy (e.g. content analysis , correlation analysis, regression)

If these words have got your head spinning, don’t worry! We’ll explain these in plain language in other posts. It’s not essential that you understand the intricacies of research design (yet!). The key takeaway here is that you’ll need to make decisions about how you’ll design your own research, and you’ll need to describe (and justify) your decisions in your methodology chapter.

2 – Execute: Collect and analyse your data

Once you’ve worked out your research design, you’ll put it into action and start collecting your data. This might mean undertaking interviews, hosting an online survey or any other data collection method. Data collection can take quite a bit of time (especially if you host in-person interviews), so be sure to factor sufficient time into your project plan for this. Oftentimes, things don’t go 100% to plan (for example, you don’t get as many survey responses as you hoped for), so bake a little extra time into your budget here.

Once you’ve collected your data, you’ll need to do some data preparation before you can sink your teeth into the analysis. For example:

• If you carry out interviews or focus groups, you’ll need to transcribe your audio data to text (i.e. a Word document).
• If you collect quantitative survey data, you’ll need to clean up your data and get it into the right format for whichever analysis software you use (for example, SPSS, R or STATA).

Once you’ve completed your data prep, you’ll undertake your analysis, using the techniques that you described in your methodology. Depending on what you find in your analysis, you might also do some additional forms of analysis that you hadn’t planned for. For example, you might see something in the data that raises new questions or that requires clarification with further analysis.

The type(s) of analysis that you’ll use depend entirely on the nature of your research and your research questions. For example:

• If your research if exploratory in nature, you’ll often use qualitative analysis techniques .
• If your research is confirmatory in nature, you’ll often use quantitative analysis techniques
• If your research involves a mix of both, you might use a mixed methods approach

Again, if these words have got your head spinning, don’t worry! We’ll explain these concepts and techniques in other posts. The key takeaway is simply that there’s no “one size fits all” for research design and methodology – it all depends on your topic, your research questions and your data. So, don’t be surprised if your study colleagues take a completely different approach to yours.

Step 7: Present your findings

Once you’ve completed your analysis, it’s time to present your findings (finally!). In a dissertation or thesis, you’ll typically present your findings in two chapters – the results chapter and the discussion chapter .

What’s the difference between the results chapter and the discussion chapter?

While these two chapters are similar, the results chapter generally just presents the processed data neatly and clearly without interpretation, while the discussion chapter explains the story the data are telling  – in other words, it provides your interpretation of the results.

For example, if you were researching the factors that influence consumer trust, you might have used a quantitative approach to identify the relationship between potential factors (e.g. perceived integrity and competence of the organisation) and consumer trust. In this case:

• Your results chapter would just present the results of the statistical tests. For example, correlation results or differences between groups. In other words, the processed numbers.
• Your discussion chapter would explain what the numbers mean in relation to your research question(s). For example, Factor 1 has a weak relationship with consumer trust, while Factor 2 has a strong relationship.

Depending on the university and degree, these two chapters (results and discussion) are sometimes merged into one , so be sure to check with your institution what their preference is. Regardless of the chapter structure, this section is about presenting the findings of your research in a clear, easy to understand fashion.

Importantly, your discussion here needs to link back to your research questions (which you outlined in the introduction or literature review chapter). In other words, it needs to answer the key questions you asked (or at least attempt to answer them).

For example, if we look at the sample research topic:

In this case, the discussion section would clearly outline which factors seem to have a noteworthy influence on organisational trust. By doing so, they are answering the overarching question and fulfilling the purpose of the research .

For more information about the results chapter , check out this post for qualitative studies and this post for quantitative studies .

Step 8: The Final Step Draw a conclusion and discuss the implications

Last but not least, you’ll need to wrap up your research with the conclusion chapter . In this chapter, you’ll bring your research full circle by highlighting the key findings of your study and explaining what the implications of these findings are.

What exactly are key findings? The key findings are those findings which directly relate to your original research questions and overall research objectives (which you discussed in your introduction chapter). The implications, on the other hand, explain what your findings mean for industry, or for research in your area.

Sticking with the consumer trust topic example, the conclusion might look something like this:

Key findings

This study set out to identify which factors influence consumer-based trust in British low-cost online equity brokerage firms. The results suggest that the following factors have a large impact on consumer trust:

While the following factors have a very limited impact on consumer trust:

Notably, within the 25-30 age groups, Factors E had a noticeably larger impact, which may be explained by…

Implications

The findings having noteworthy implications for British low-cost online equity brokers. Specifically:

The large impact of Factors X and Y implies that brokers need to consider….

The limited impact of Factor E implies that brokers need to…

As you can see, the conclusion chapter is basically explaining the “what” (what your study found) and the “so what?” (what the findings mean for the industry or research). This brings the study full circle and closes off the document.

Let’s recap – how to write a dissertation or thesis

You’re still with me? Impressive! I know that this post was a long one, but hopefully you’ve learnt a thing or two about how to write a dissertation or thesis, and are now better equipped to start your own research.

To recap, the 8 steps to writing a quality dissertation (or thesis) are as follows:

• Understand what a dissertation (or thesis) is – a research project that follows the research process.
• Find a unique (original) and important research topic
• Craft a convincing dissertation or thesis research proposal
• Write a clear, compelling introduction chapter
• Undertake a thorough review of the existing research and write up a literature review
• Undertake your own research
• Present and interpret your findings

Once you’ve wrapped up the core chapters, all that’s typically left is the abstract , reference list and appendices. As always, be sure to check with your university if they have any additional requirements in terms of structure or content.  

Psst... there’s more!

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

20 Comments

thankfull >>>this is very useful

Thank you, it was really helpful

unquestionably, this amazing simplified way of teaching. Really , I couldn’t find in the literature words that fully explicit my great thanks to you. However, I could only say thanks a-lot.

Great to hear that – thanks for the feedback. Good luck writing your dissertation/thesis.

This is the most comprehensive explanation of how to write a dissertation. Many thanks for sharing it free of charge.

Very rich presentation. Thank you

Thanks Derek Jansen|GRADCOACH, I find it very useful guide to arrange my activities and proceed to research!

Thank you so much for such a marvelous teaching .I am so convinced that am going to write a comprehensive and a distinct masters dissertation

It is an amazing comprehensive explanation

This was straightforward. Thank you!

I can say that your explanations are simple and enlightening – understanding what you have done here is easy for me. Could you write more about the different types of research methods specific to the three methodologies: quan, qual and MM. I look forward to interacting with this website more in the future.

Thanks for the feedback and suggestions 🙂

Hello, your write ups is quite educative. However, l have challenges in going about my research questions which is below; *Building the enablers of organisational growth through effective governance and purposeful leadership.*

Very educating.

Just listening to the name of the dissertation makes the student nervous. As writing a top-quality dissertation is a difficult task as it is a lengthy topic, requires a lot of research and understanding and is usually around 10,000 to 15000 words. Sometimes due to studies, unbalanced workload or lack of research and writing skill students look for dissertation submission from professional writers.

Thank you 💕😊 very much. I was confused but your comprehensive explanation has cleared my doubts of ever presenting a good thesis. Thank you.

thank you so much, that was so useful

Hi. Where is the excel spread sheet ark?

could you please help me look at your thesis paper to enable me to do the portion that has to do with the specification

my topic is “the impact of domestic revenue mobilization.

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

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  

1751 Accesses

1 Citations

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime
• Available as PDF
• Read on any device
• Instant download
• Own it forever
• Available as EPUB and PDF
• Durable hardcover edition
• Dispatched in 3 to 5 business days
• Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Quantitative Research

Case Study 3: Application of Quantitative Methodology

Bhaumik S, Arora M, Singh A, Sargent JD. Impact of entertainment media smoking on adolescent smoking behaviours. Cochrane Database Syst Rev. 2015;6:1–12. https://doi.org/10.1002/14651858.CD011720 .

Article   Google Scholar  

Dickersin K, Manheimer E, Wieland S, Robinson KA, Lefebvre C, McDonald S. Development of the Cochrane Collaboration’s CENTRAL register of controlled clinical trials. Eval Health Prof. 2002;25(1):38–64.

Google Scholar  

Docherty M, Smith R. The case for structuring the discussion of scientific papers: much the same as that for structuring abstracts. Br Med J. 1999;318(7193):1224–5.

Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology. 1999;10(1):37–48.

Horton R. The rhetoric of research. Br Med J. 1995;310(6985):985–7.

Kool B, Ziersch A, Robinson P, Wolfenden L, Lowe JB. The ‘Seven deadly sins’ of rejected papers. Aust N Z J Public Health. 2016;40(1):3–4.

Mannocci A, Saulle R, Colamesta V, D’Aguanno S, Giraldi G, Maffongelli E, et al. What is the impact of reporting guidelines on public health journals in Europe? The case of STROBE, CONSORT and PRISMA. J Public Health. 2015;37(4):737–40.

Rothwell PM. External validity of randomised controlled trials: “to whom do the results of this trial apply?”. Lancet. 2005;365(9453):82–93.

Schulz KF, Altman DG, Moher D. CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. PLoS Med. 2010;7(3):e1000251.

Szklo M. Quality of scientific articles. Rev Saude Publica. 2006;40 Spec no:30–5.

Vandenbroucke JP, von Elm E, Altman DG, Gotzsche PC, Mulrow CD, Pocock SJ, et al. Strengthening the reporting of observational studies in epidemiology (STROBE): explanation and elaboration. PLoS Med. 2007;4(10):e297.

Weiss NS, Koepsell TD, Psaty BM. Generalizability of the results of randomized trials. Arch Intern Med. 2008;168(2):133–5.

Singh A, Gupta A, Peres MA, Watt RG, Tsakos G, Mathur MR. Association between tooth loss and hypertension among a primarily rural middle aged and older Indian adult population. J Public Health Dent. 2016;76:198–205.

Download references

Author information

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

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Ankur Singh .

Editor information

Editors and affiliations.

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

Pranee Liamputtong

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this entry

Cite this entry.

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

Download citation

DOI : https://doi.org/10.1007/978-981-10-5251-4_117

Published : 13 January 2019

Publisher Name : Springer, Singapore

Print ISBN : 978-981-10-5250-7

Online ISBN : 978-981-10-5251-4

eBook Packages : Social Sciences Reference Module Humanities and Social Sciences Reference Module Business, Economics and Social Sciences

Share this entry

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Publish with us

Policies and ethics

• Find a journal
• Track your research

Dissertation Research—Planning, Researching, Publishing

• Getting Started
• Find Dissertations
• Dissertation Process
• Library Database Searching
• Staying Current
• Qualitative
• Quantitive Research
• Mixed Methods Research
• Dissertation & Fellowship Funding

Quantitative Research is a "means for testing objective theories by examining the relationships among variables.  These variables, in turn, can be measured, typically on instruments, so that numbered data can be analyzed using statistical procedures.  The final written report has a set structure consisting of introduction, literature and theory, methods, results and discussion"  ( Creswell, 2007 ) .

Quantitative Research Books

Below is a sampling of books on the subject of "quantitave research" owned by GW and consortium libraries. Click the book image and it will take you to the item in the library catalog, where you can request it.

Journal Article Search Terms

Below is a list of keywords to use when searching for various aspects of quantitative research.

Combine one of these keywords with your topic when you search in one of the library's SUBJECT DATABASES

Subject Guide

• << Previous: Qualitative
• Next: Mixed Methods Research >>
• Last Updated: Jun 5, 2024 2:48 PM
• URL: https://libguides.gwu.edu/dissertation

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base
• Dissertation
• Dissertation & Thesis Outline | Example & Free Templates

Dissertation & Thesis Outline | Example & Free Templates

Published on June 7, 2022 by Tegan George . Revised on November 21, 2023.

A thesis or dissertation outline is one of the most critical early steps in your writing process . It helps you to lay out and organize your ideas and can provide you with a roadmap for deciding the specifics of your dissertation topic and showcasing its relevance to your field.

Generally, an outline contains information on the different sections included in your thesis or dissertation , such as:

• Your anticipated title
• Your abstract
• Your chapters (sometimes subdivided into further topics like literature review, research methods, avenues for future research, etc.)

In the final product, you can also provide a chapter outline for your readers. This is a short paragraph at the end of your introduction to inform readers about the organizational structure of your thesis or dissertation. This chapter outline is also known as a reading guide or summary outline.

Table of contents

How to outline your thesis or dissertation, dissertation and thesis outline templates, chapter outline example, sample sentences for your chapter outline, sample verbs for variation in your chapter outline, other interesting articles, frequently asked questions about thesis and dissertation outlines.

While there are some inter-institutional differences, many outlines proceed in a fairly similar fashion.

• Working Title
• “Elevator pitch” of your work (often written last).
• Introduce your area of study, sharing details about your research question, problem statement , and hypotheses . Situate your research within an existing paradigm or conceptual or theoretical framework .
• Subdivide as you see fit into main topics and sub-topics.
• Describe your research methods (e.g., your scope , population , and data collection ).
• Present your research findings and share about your data analysis methods.
• Answer the research question in a concise way.
• Interpret your findings, discuss potential limitations of your own research and speculate about future implications or related opportunities.

For a more detailed overview of chapters and other elements, be sure to check out our article on the structure of a dissertation or download our template .

To help you get started, we’ve created a full thesis or dissertation template in Word or Google Docs format. It’s easy adapt it to your own requirements.

 Download Word template    Download Google Docs template

It can be easy to fall into a pattern of overusing the same words or sentence constructions, which can make your work monotonous and repetitive for your readers. Consider utilizing some of the alternative constructions presented below.

Example 1: Passive construction

The passive voice is a common choice for outlines and overviews because the context makes it clear who is carrying out the action (e.g., you are conducting the research ). However, overuse of the passive voice can make your text vague and imprecise.

Example 2: IS-AV construction

You can also present your information using the “IS-AV” (inanimate subject with an active verb ) construction.

A chapter is an inanimate object, so it is not capable of taking an action itself (e.g., presenting or discussing). However, the meaning of the sentence is still easily understandable, so the IS-AV construction can be a good way to add variety to your text.

Example 3: The “I” construction

Another option is to use the “I” construction, which is often recommended by style manuals (e.g., APA Style and Chicago style ). However, depending on your field of study, this construction is not always considered professional or academic. Ask your supervisor if you’re not sure.

Example 4: Mix-and-match

To truly make the most of these options, consider mixing and matching the passive voice , IS-AV construction , and “I” construction .This can help the flow of your argument and improve the readability of your text.

As you draft the chapter outline, you may also find yourself frequently repeating the same words, such as “discuss,” “present,” “prove,” or “show.” Consider branching out to add richness and nuance to your writing. Here are some examples of synonyms you can use.

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

Research bias

• Anchoring bias
• Halo effect
• The Baader–Meinhof phenomenon
• The placebo effect
• Nonresponse bias
• Deep learning
• Generative AI
• Machine learning
• Reinforcement learning
• Supervised vs. unsupervised learning

 (AI) Tools

• Grammar Checker
• Paraphrasing Tool
• Text Summarizer
• AI Detector
• Plagiarism Checker
• Citation Generator

When you mention different chapters within your text, it’s considered best to use Roman numerals for most citation styles. However, the most important thing here is to remain consistent whenever using numbers in your dissertation .

The title page of your thesis or dissertation goes first, before all other content or lists that you may choose to include.

A thesis or dissertation outline is one of the most critical first steps in your writing process. It helps you to lay out and organize your ideas and can provide you with a roadmap for deciding what kind of research you’d like to undertake.

• Your chapters (sometimes subdivided into further topics like literature review , research methods , avenues for future research, etc.)

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

George, T. (2023, November 21). Dissertation & Thesis Outline | Example & Free Templates. Scribbr. Retrieved August 29, 2024, from https://www.scribbr.com/dissertation/dissertation-thesis-outline/

Is this article helpful?

Tegan George

Other students also liked, dissertation table of contents in word | instructions & examples, figure and table lists | word instructions, template & examples, thesis & dissertation acknowledgements | tips & examples, "i thought ai proofreading was useless but..".

I've been using Scribbr for years now and I know it's a service that won't disappoint. It does a good job spotting mistakes”

•   Ubrisa Home
• Faculty of Education
• Educational Foundations
• Research articles (Dept of Educational Foundations)

Show simple item record

Writing a quantitative research thesis

Files in this item

This item appears in the following Collection(s)

• Research articles (Dept of Educational Foundations) [46]

Show Statistical Information

• Resources Home 🏠
• Try SciSpace Copilot
• Search research papers
• Add Copilot Extension
• Try AI Detector
• Try Paraphraser
• Try Citation Generator
• April Papers
• June Papers
• July Papers

What is a thesis | A Complete Guide with Examples

Table of Contents

A thesis is a comprehensive academic paper based on your original research that presents new findings, arguments, and ideas of your study. It’s typically submitted at the end of your master’s degree or as a capstone of your bachelor’s degree.

However, writing a thesis can be laborious, especially for beginners. From the initial challenge of pinpointing a compelling research topic to organizing and presenting findings, the process is filled with potential pitfalls.

Therefore, to help you, this guide talks about what is a thesis. Additionally, it offers revelations and methodologies to transform it from an overwhelming task to a manageable and rewarding academic milestone.

What is a thesis?

A thesis is an in-depth research study that identifies a particular topic of inquiry and presents a clear argument or perspective about that topic using evidence and logic.

Writing a thesis showcases your ability of critical thinking, gathering evidence, and making a compelling argument. Integral to these competencies is thorough research, which not only fortifies your propositions but also confers credibility to your entire study.

Furthermore, there's another phenomenon you might often confuse with the thesis: the ' working thesis .' However, they aren't similar and shouldn't be used interchangeably.

A working thesis, often referred to as a preliminary or tentative thesis, is an initial version of your thesis statement. It serves as a draft or a starting point that guides your research in its early stages.

As you research more and gather more evidence, your initial thesis (aka working thesis) might change. It's like a starting point that can be adjusted as you learn more. It's normal for your main topic to change a few times before you finalize it.

While a thesis identifies and provides an overarching argument, the key to clearly communicating the central point of that argument lies in writing a strong thesis statement.

What is a thesis statement?

A strong thesis statement (aka thesis sentence) is a concise summary of the main argument or claim of the paper. It serves as a critical anchor in any academic work, succinctly encapsulating the primary argument or main idea of the entire paper.

Typically found within the introductory section, a strong thesis statement acts as a roadmap of your thesis, directing readers through your arguments and findings. By delineating the core focus of your investigation, it offers readers an immediate understanding of the context and the gravity of your study.

Furthermore, an effectively crafted thesis statement can set forth the boundaries of your research, helping readers anticipate the specific areas of inquiry you are addressing.

Different types of thesis statements

A good thesis statement is clear, specific, and arguable. Therefore, it is necessary for you to choose the right type of thesis statement for your academic papers.

Thesis statements can be classified based on their purpose and structure. Here are the primary types of thesis statements:

Argumentative (or Persuasive) thesis statement

Purpose : To convince the reader of a particular stance or point of view by presenting evidence and formulating a compelling argument.

Example : Reducing plastic use in daily life is essential for environmental health.

Analytical thesis statement

Purpose : To break down an idea or issue into its components and evaluate it.

Example : By examining the long-term effects, social implications, and economic impact of climate change, it becomes evident that immediate global action is necessary.

Expository (or Descriptive) thesis statement

Purpose : To explain a topic or subject to the reader.

Example : The Great Depression, spanning the 1930s, was a severe worldwide economic downturn triggered by a stock market crash, bank failures, and reduced consumer spending.

Cause and effect thesis statement

Purpose : To demonstrate a cause and its resulting effect.

Example : Overuse of smartphones can lead to impaired sleep patterns, reduced face-to-face social interactions, and increased levels of anxiety.

Compare and contrast thesis statement

Purpose : To highlight similarities and differences between two subjects.

Example : "While both novels '1984' and 'Brave New World' delve into dystopian futures, they differ in their portrayal of individual freedom, societal control, and the role of technology."

When you write a thesis statement , it's important to ensure clarity and precision, so the reader immediately understands the central focus of your work.

What is the difference between a thesis and a thesis statement?

While both terms are frequently used interchangeably, they have distinct meanings.

A thesis refers to the entire research document, encompassing all its chapters and sections. In contrast, a thesis statement is a brief assertion that encapsulates the central argument of the research.

Here’s an in-depth differentiation table of a thesis and a thesis statement.

Now, to craft a compelling thesis, it's crucial to adhere to a specific structure. Let’s break down these essential components that make up a thesis structure

15 components of a thesis structure

Navigating a thesis can be daunting. However, understanding its structure can make the process more manageable.

Here are the key components or different sections of a thesis structure:

Your thesis begins with the title page. It's not just a formality but the gateway to your research.

Here, you'll prominently display the necessary information about you (the author) and your institutional details.

• Title of your thesis
• Your full name
• Your department
• Your institution and degree program
• Your submission date
• Your Supervisor's name (in some cases)
• Your Department or faculty (in some cases)
• Your University's logo (in some cases)
• Your Student ID (in some cases)

In a concise manner, you'll have to summarize the critical aspects of your research in typically no more than 200-300 words.

This includes the problem statement, methodology, key findings, and conclusions. For many, the abstract will determine if they delve deeper into your work, so ensure it's clear and compelling.

Acknowledgments

Research is rarely a solitary endeavor. In the acknowledgments section, you have the chance to express gratitude to those who've supported your journey.

This might include advisors, peers, institutions, or even personal sources of inspiration and support. It's a personal touch, reflecting the humanity behind the academic rigor.

Table of contents

A roadmap for your readers, the table of contents lists the chapters, sections, and subsections of your thesis.

By providing page numbers, you allow readers to navigate your work easily, jumping to sections that pique their interest.

List of figures and tables

Research often involves data, and presenting this data visually can enhance understanding. This section provides an organized listing of all figures and tables in your thesis.

It's a visual index, ensuring that readers can quickly locate and reference your graphical data.

Introduction

Here's where you introduce your research topic, articulate the research question or objective, and outline the significance of your study.

• Present the research topic : Clearly articulate the central theme or subject of your research.
• Background information : Ground your research topic, providing any necessary context or background information your readers might need to understand the significance of your study.
• Define the scope : Clearly delineate the boundaries of your research, indicating what will and won't be covered.
• Literature review : Introduce any relevant existing research on your topic, situating your work within the broader academic conversation and highlighting where your research fits in.
• State the research Question(s) or objective(s) : Clearly articulate the primary questions or objectives your research aims to address.
• Outline the study's structure : Give a brief overview of how the subsequent sections of your work will unfold, guiding your readers through the journey ahead.

The introduction should captivate your readers, making them eager to delve deeper into your research journey.

Literature review section

Your study correlates with existing research. Therefore, in the literature review section, you'll engage in a dialogue with existing knowledge, highlighting relevant studies, theories, and findings.

It's here that you identify gaps in the current knowledge, positioning your research as a bridge to new insights.

To streamline this process, consider leveraging AI tools. For example, the SciSpace literature review tool enables you to efficiently explore and delve into research papers, simplifying your literature review journey.

Methodology

In the research methodology section, you’ll detail the tools, techniques, and processes you employed to gather and analyze data. This section will inform the readers about how you approached your research questions and ensures the reproducibility of your study.

Here's a breakdown of what it should encompass:

• Research Design : Describe the overall structure and approach of your research. Are you conducting a qualitative study with in-depth interviews? Or is it a quantitative study using statistical analysis? Perhaps it's a mixed-methods approach?
• Data Collection : Detail the methods you used to gather data. This could include surveys, experiments, observations, interviews, archival research, etc. Mention where you sourced your data, the duration of data collection, and any tools or instruments used.
• Sampling : If applicable, explain how you selected participants or data sources for your study. Discuss the size of your sample and the rationale behind choosing it.
• Data Analysis : Describe the techniques and tools you used to process and analyze the data. This could range from statistical tests in quantitative research to thematic analysis in qualitative research.
• Validity and Reliability : Address the steps you took to ensure the validity and reliability of your findings to ensure that your results are both accurate and consistent.
• Ethical Considerations : Highlight any ethical issues related to your research and the measures you took to address them, including — informed consent, confidentiality, and data storage and protection measures.

Moreover, different research questions necessitate different types of methodologies. For instance:

• Experimental methodology : Often used in sciences, this involves a controlled experiment to discern causality.
• Qualitative methodology : Employed when exploring patterns or phenomena without numerical data. Methods can include interviews, focus groups, or content analysis.
• Quantitative methodology : Concerned with measurable data and often involves statistical analysis. Surveys and structured observations are common tools here.
• Mixed methods : As the name implies, this combines both qualitative and quantitative methodologies.

The Methodology section isn’t just about detailing the methods but also justifying why they were chosen. The appropriateness of the methods in addressing your research question can significantly impact the credibility of your findings.

Results (or Findings)

This section presents the outcomes of your research. It's crucial to note that the nature of your results may vary; they could be quantitative, qualitative, or a mix of both.

Quantitative results often present statistical data, showcasing measurable outcomes, and they benefit from tables, graphs, and figures to depict these data points.

Qualitative results , on the other hand, might delve into patterns, themes, or narratives derived from non-numerical data, such as interviews or observations.

Regardless of the nature of your results, clarity is essential. This section is purely about presenting the data without offering interpretations — that comes later in the discussion.

In the discussion section, the raw data transforms into valuable insights.

Start by revisiting your research question and contrast it with the findings. How do your results expand, constrict, or challenge current academic conversations?

Dive into the intricacies of the data, guiding the reader through its implications. Detail potential limitations transparently, signaling your awareness of the research's boundaries. This is where your academic voice should be resonant and confident.

Practical implications (Recommendation) section

Based on the insights derived from your research, this section provides actionable suggestions or proposed solutions.

Whether aimed at industry professionals or the general public, recommendations translate your academic findings into potential real-world actions. They help readers understand the practical implications of your work and how it can be applied to effect change or improvement in a given field.

When crafting recommendations, it's essential to ensure they're feasible and rooted in the evidence provided by your research. They shouldn't merely be aspirational but should offer a clear path forward, grounded in your findings.

The conclusion provides closure to your research narrative.

It's not merely a recap but a synthesis of your main findings and their broader implications. Reconnect with the research questions or hypotheses posited at the beginning, offering clear answers based on your findings.

Reflect on the broader contributions of your study, considering its impact on the academic community and potential real-world applications.

Lastly, the conclusion should leave your readers with a clear understanding of the value and impact of your study.

References (or Bibliography)

Every theory you've expounded upon, every data point you've cited, and every methodological precedent you've followed finds its acknowledgment here.

In references, it's crucial to ensure meticulous consistency in formatting, mirroring the specific guidelines of the chosen citation style .

Proper referencing helps to avoid plagiarism , gives credit to original ideas, and allows readers to explore topics of interest. Moreover, it situates your work within the continuum of academic knowledge.

To properly cite the sources used in the study, you can rely on online citation generator tools  to generate accurate citations!

Here’s more on how you can cite your sources.

Often, the depth of research produces a wealth of material that, while crucial, can make the core content of the thesis cumbersome. The appendix is where you mention extra information that supports your research but isn't central to the main text.

Whether it's raw datasets, detailed procedural methodologies, extended case studies, or any other ancillary material, the appendices ensure that these elements are archived for reference without breaking the main narrative's flow.

For thorough researchers and readers keen on meticulous details, the appendices provide a treasure trove of insights.

Glossary (optional)

In academics, specialized terminologies, and jargon are inevitable. However, not every reader is versed in every term.

The glossary, while optional, is a critical tool for accessibility. It's a bridge ensuring that even readers from outside the discipline can access, understand, and appreciate your work.

By defining complex terms and providing context, you're inviting a wider audience to engage with your research, enhancing its reach and impact.

Remember, while these components provide a structured framework, the essence of your thesis lies in the originality of your ideas, the rigor of your research, and the clarity of your presentation.

As you craft each section, keep your readers in mind, ensuring that your passion and dedication shine through every page.

Thesis examples

To further elucidate the concept of a thesis, here are illustrative examples from various fields:

Example 1 (History): Abolition, Africans, and Abstraction: the Influence of the ‘Noble Savage’ on British and French Antislavery Thought, 1787-1807 by Suchait Kahlon.

Example 2 (Climate Dynamics): Influence of external forcings on abrupt millennial-scale climate changes: a statistical modelling study by Takahito Mitsui · Michel Crucifix

Checklist for your thesis evaluation

Evaluating your thesis ensures that your research meets the standards of academia. Here's an elaborate checklist to guide you through this critical process.

Content and structure

• Is the thesis statement clear, concise, and debatable?
• Does the introduction provide sufficient background and context?
• Is the literature review comprehensive, relevant, and well-organized?
• Does the methodology section clearly describe and justify the research methods?
• Are the results/findings presented clearly and logically?
• Does the discussion interpret the results in light of the research question and existing literature?
• Is the conclusion summarizing the research and suggesting future directions or implications?

Clarity and coherence

• Is the writing clear and free of jargon?
• Are ideas and sections logically connected and flowing?
• Is there a clear narrative or argument throughout the thesis?

Research quality

• Is the research question significant and relevant?
• Are the research methods appropriate for the question?
• Is the sample size (if applicable) adequate?
• Are the data analysis techniques appropriate and correctly applied?
• Are potential biases or limitations addressed?

Originality and significance

• Does the thesis contribute new knowledge or insights to the field?
• Is the research grounded in existing literature while offering fresh perspectives?

Formatting and presentation

• Is the thesis formatted according to institutional guidelines?
• Are figures, tables, and charts clear, labeled, and referenced in the text?
• Is the bibliography or reference list complete and consistently formatted?
• Are appendices relevant and appropriately referenced in the main text?

Grammar and language

• Is the thesis free of grammatical and spelling errors?
• Is the language professional, consistent, and appropriate for an academic audience?
• Are quotations and paraphrased material correctly cited?

Feedback and revision

• Have you sought feedback from peers, advisors, or experts in the field?
• Have you addressed the feedback and made the necessary revisions?

Overall assessment

• Does the thesis as a whole feel cohesive and comprehensive?
• Would the thesis be understandable and valuable to someone in your field?

Ensure to use this checklist to leave no ground for doubt or missed information in your thesis.

After writing your thesis, the next step is to discuss and defend your findings verbally in front of a knowledgeable panel. You’ve to be well prepared as your professors may grade your presentation abilities.

Preparing your thesis defense

A thesis defense, also known as "defending the thesis," is the culmination of a scholar's research journey. It's the final frontier, where you’ll present their findings and face scrutiny from a panel of experts.

Typically, the defense involves a public presentation where you’ll have to outline your study, followed by a question-and-answer session with a committee of experts. This committee assesses the validity, originality, and significance of the research.

The defense serves as a rite of passage for scholars. It's an opportunity to showcase expertise, address criticisms, and refine arguments. A successful defense not only validates the research but also establishes your authority as a researcher in your field.

Here’s how you can effectively prepare for your thesis defense .

Now, having touched upon the process of defending a thesis, it's worth noting that scholarly work can take various forms, depending on academic and regional practices.

One such form, often paralleled with the thesis, is the 'dissertation.' But what differentiates the two?

Dissertation vs. Thesis

Often used interchangeably in casual discourse, they refer to distinct research projects undertaken at different levels of higher education.

To the uninitiated, understanding their meaning might be elusive. So, let's demystify these terms and delve into their core differences.

Here's a table differentiating between the two.

Wrapping up

From understanding the foundational concept of a thesis to navigating its various components, differentiating it from a dissertation, and recognizing the importance of proper citation — this guide covers it all.

As scholars and readers, understanding these nuances not only aids in academic pursuits but also fosters a deeper appreciation for the relentless quest for knowledge that drives academia.

It’s important to remember that every thesis is a testament to curiosity, dedication, and the indomitable spirit of discovery.

Good luck with your thesis writing!

Frequently Asked Questions

A thesis typically ranges between 40-80 pages, but its length can vary based on the research topic, institution guidelines, and level of study.

A PhD thesis usually spans 200-300 pages, though this can vary based on the discipline, complexity of the research, and institutional requirements.

To identify a thesis topic, consider current trends in your field, gaps in existing literature, personal interests, and discussions with advisors or mentors. Additionally, reviewing related journals and conference proceedings can provide insights into potential areas of exploration.

The conceptual framework is often situated in the literature review or theoretical framework section of a thesis. It helps set the stage by providing the context, defining key concepts, and explaining the relationships between variables.

A thesis statement should be concise, clear, and specific. It should state the main argument or point of your research. Start by pinpointing the central question or issue your research addresses, then condense that into a single statement, ensuring it reflects the essence of your paper.

You might also like

Smallpdf vs SciSpace: Which ChatPDF is Right for You?

Adobe PDF Reader vs. SciSpace ChatPDF — ChatPDF Showdown

Boosting Citations: A Comparative Analysis of Graphical Abstract vs. Video Abstract

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Writing a Quantitative Research Thesis

Research is an exciting adventure which if properly carried out adds richly to the student’s experience, to the school academic prestige and to the society through the new knowledge it creates which could be applied in solving related problems and in other services. Young researchers always encounter problems designing and carrying out their first study which usually is their project, thesis or dissertation. Some who are not properly guided or supervised get frustrated and drop out of their programmes because of these problems. The ideas in this paper which metamorphosed over 25 years of teaching and supervising research, represents an attempt to contribute to the solution of such problems especially for graduate students. It presents elaborately, in very simple language and in five sections, the practical steps that should guide beginning researchers on how to carry out their study and report it.

Related Papers

Fred Ntedika Mvumbi

A thesis/Dissertation, as one piece of work, should be a text that addresses the issues of the community; all divisions and sub-divisions ought to be interconnected and interrelated to become a process leading to one goal. Thus, the text has threefold dimension. The first is that few people know the underlying principle of a research; that is the wisdom behind the idea, the efforts and the pains of carrying out a research in a particular field of knowledge. The second is a request to students to fall in love and to have passion for the kind of study they want to undertake; this increases the motivation and disposes them to go extra miles for comprehensive and immense discovery where understanding, application and generation of new knowledge take place. The third reason, which is equally important, maybe the most important in writing this text, concerns the organization of the report; in this case the presentation of a thesis/dissertation. Students should be more and more motivated to carry out research in various fields of knowledge, particularly when they have means; and postgraduate students should be increasingly encouraged to take part in research initiatives, for this helps to find new meanings of life.

Kezang sherab

khadidja Hammoudi

andrea azures

• Identify the interest • Study the interest • Identify possible interesting dimension or problem in the area of interest • Formulate the initial research question in response to the identified dimension or problem in the area of interest • Make an initial research to gain further understanding of the initial research question • Incorporate new findings to the initial research question • Assess whether the research question remains relevant to the area of interest by studying the current state of literature All research inquiry starts from a simple identification of an area on which someone is interested in. A student researcher could be interested in the current state of information and communication technology, educational system, career tracks, use of social media, effects of personal issues on academic performance and impact of social background on education opportunities to name a few. Interests are either developed through life path, innate (such as inclination to music and other performing arts) or ideologically acquired. The identification of interest as the first stage of research inquiry is only reasonable since demands of the process requires undivided commitment and human nature has it that we struggle doing things when it is outside our area of interest.

WORLD EDUCATION CONNECT Multidisciplinary e-Publication

JAYSON S . DIGAMON

It provides any reader procedures in making research questions that are cursorily discussed in graduate school, especially during thesis writing. The author hopes that this module will facilitate students' fluid making of research questions which form part of the essentials in writing the entire research output.

Munyaradzi Moyo

Essential Tremor

So you’re a student at university looking to do research and write a dissertation (thesis)? This book is for you. It’s an essential guide to the research process covering all stages from planning to doing to writing up and proofing. The book also has a unique section on publishing your dissertation for those who wish to push their academic career along. Unlike other books, it does not assume that you have infinite time and resources to conduct your research. It recognises that at this level you probably have six months or less to finish the dissertation and gives practical advice on which studies are feasible and which are not. The book gets on top of the research terminology by giving concise, working definitions of the key terms, which will appeal to international students. With over 30 years of experience in leading and teaching research in a variety of fields, Dr Michael Cribb has pulled together all his wisdom and knowledge in one book to help guide students through their first big research project.

Khawaja Mudasir Mehmood

imane ghazlane

Regardless of the discipline or institution in which the scientific research was carried out, the &quot;method&quot; section is present. However, many research works lack relevance and suffer from methodological problems. However, method remains the foundation of all research work that can inevitably influence results that can affect problem solving, national development, and threaten our quality of life in general. This work is an exploratory study of research methods used in graduation projects in the following disciplines (health sciences, engineering, biological and agronomic sciences, economic and social sciences). The method used in this work is based on three investigative tools: (a) comparison of national scientific production according to a few references (b) semi-structured survey by interviewing supervisors of final dissertations and theses in different selected disciplines (b) systematic analysis of fifty final dissertations. The works was obtained from the libraries of ...

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED PAPERS

Avinash Advani

SAMSUDIN N. ABDULLAH, PhD, MOHAMAD T. SIMPAL, MAST & ARJEY B. MANGAKOY

SAMSUDIN N ABDULLAH, PhD

Dr Sunarsih

EMOs Tanzania

martinus hartonio

Sekar Haranii

CV.Haura Utama

Dwi Astuti Wahyu Nurhayati

Open University Research Sessions

Dr. Inoka Deepthinee Dediwala

mahrukh fatima

natnael getu

The Cyprus Journal of Sciences

Kakia Avgousti

SOCIETY. INTEGRATION. EDUCATION. Proceedings of the International Scientific Conference

Mirdza Paipare

melaku emayneh

Scientific Research Publishing: Creative Education

Dr. Qais Faryadi

Journal of Information Management and Practices

Nareen Hashmi

Riccardo Pelizzo

Daniel Kashikola

South African Dental Journal

Leanne Sykes

International Journal of Research

Enas Abuhamda , Islam Asim Ismail

mark vince agacite

Fauzul Azhimah

Review of Applied Management and Social Sciences

hassan raza

Bhimashankar Sanga

RELATED TOPICS

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

• DOI: 10.1080/09751122.2009.11889972
• Corpus ID: 142974994

Writing a Quantitative Research Thesis

• Published 8 April 2009
• Education, Mathematics
• International Journal of Educational Sciences

66 Citations

Students’ level of critical thinking skills (cts) in writing problem statement (ps) in theses.

• Highly Influenced

Facilitating the PhD Research Process: Guides for Identifying Research Problem and Establishing Research Gap

An overview of quantitative research methods, an analysis of the relationship between library use and student's achievement at a master level, rhetorical moves in problem statement section of iranian efl postgraduate students' theses, needs analysis of interactive digital books based on project at biological learning and strategy learning designs subject, implementation of self-assessment to know the level of student's learning motivation in following online learning, student motivation against using guided inquiry-based animal physiology practicum guide, rhetorical structure in the problem statement section of iranian postgraduate students' research projects, affect vs cognition as antecedents of selection behaviour of elective courses using fsqca, 29 references, understanding educational research, foundations of behavioral research, the problem at hand, handbook in research and evaluation, ethical standards., nursing research. principles and methods: 7th edition, assumptions, educational research : the art and science of investigation, foundations of educational research, related papers.

Showing 1 through 3 of 0 Related Papers

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Korean Med Sci
• v.38(37); 2023 Sep 18
• PMC10506897

Conducting and Writing Quantitative and Qualitative Research

Edward barroga.

1 Department of Medical Education, Showa University School of Medicine, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

Atsuko Furuta

Makiko arima, shizuma tsuchiya, chikako kawahara, yusuke takamiya.

Comprehensive knowledge of quantitative and qualitative research systematizes scholarly research and enhances the quality of research output. Scientific researchers must be familiar with them and skilled to conduct their investigation within the frames of their chosen research type. When conducting quantitative research, scientific researchers should describe an existing theory, generate a hypothesis from the theory, test their hypothesis in novel research, and re-evaluate the theory. Thereafter, they should take a deductive approach in writing the testing of the established theory based on experiments. When conducting qualitative research, scientific researchers raise a question, answer the question by performing a novel study, and propose a new theory to clarify and interpret the obtained results. After which, they should take an inductive approach to writing the formulation of concepts based on collected data. When scientific researchers combine the whole spectrum of inductive and deductive research approaches using both quantitative and qualitative research methodologies, they apply mixed-method research. Familiarity and proficiency with these research aspects facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Graphical Abstract

INTRODUCTION

Novel research studies are conceptualized by scientific researchers first by asking excellent research questions and developing hypotheses, then answering these questions by testing their hypotheses in ethical research. 1 , 2 , 3 Before they conduct novel research studies, scientific researchers must possess considerable knowledge of both quantitative and qualitative research. 2

In quantitative research, researchers describe existing theories, generate and test a hypothesis in novel research, and re-evaluate existing theories deductively based on their experimental results. 1 , 4 , 5 In qualitative research, scientific researchers raise and answer research questions by performing a novel study, then propose new theories by clarifying their results inductively. 1 , 6

RATIONALE OF THIS ARTICLE

When researchers have a limited knowledge of both research types and how to conduct them, this can result in substandard investigation. Researchers must be familiar with both types of research and skilled to conduct their investigations within the frames of their chosen type of research. Thus, meticulous care is needed when planning quantitative and qualitative research studies to avoid unethical research and poor outcomes.

Understanding the methodological and writing assumptions 7 , 8 underpinning quantitative and qualitative research, especially by non-Anglophone researchers, is essential for their successful conduct. Scientific researchers, especially in the academe, face pressure to publish in international journals 9 where English is the language of scientific communication. 10 , 11 In particular, non-Anglophone researchers face challenges related to linguistic, stylistic, and discourse differences. 11 , 12 Knowing the assumptions of the different types of research will help clarify research questions and methodologies, easing the challenge and help.

SEARCH FOR RELEVANT ARTICLES

To identify articles relevant to this topic, we adhered to the search strategy recommended by Gasparyan et al. 7 We searched through PubMed, Scopus, Directory of Open Access Journals, and Google Scholar databases using the following keywords: quantitative research, qualitative research, mixed-method research, deductive reasoning, inductive reasoning, study design, descriptive research, correlational research, experimental research, causal-comparative research, quasi-experimental research, historical research, ethnographic research, meta-analysis, narrative research, grounded theory, phenomenology, case study, and field research.

AIMS OF THIS ARTICLE

This article aims to provide a comparative appraisal of qualitative and quantitative research for scientific researchers. At present, there is still a need to define the scope of qualitative research, especially its essential elements. 13 Consensus on the critical appraisal tools to assess the methodological quality of qualitative research remains lacking. 14 Framing and testing research questions can be challenging in qualitative research. 2 In the healthcare system, it is essential that research questions address increasingly complex situations. Therefore, research has to be driven by the kinds of questions asked and the corresponding methodologies to answer these questions. 15 The mixed-method approach also needs to be clarified as this would appear to arise from different philosophical underpinnings. 16

This article also aims to discuss how particular types of research should be conducted and how they should be written in adherence to international standards. In the US, Europe, and other countries, responsible research and innovation was conceptualized and promoted with six key action points: engagement, gender equality, science education, open access, ethics and governance. 17 , 18 International ethics standards in research 19 as well as academic integrity during doctoral trainings are now integral to the research process. 20

POTENTIAL BENEFITS FROM THIS ARTICLE

This article would be beneficial for researchers in further enhancing their understanding of the theoretical, methodological, and writing aspects of qualitative and quantitative research, and their combination.

Moreover, this article reviews the basic features of both research types and overviews the rationale for their conduct. It imparts information on the most common forms of quantitative and qualitative research, and how they are carried out. These aspects would be helpful for selecting the optimal methodology to use for research based on the researcher’s objectives and topic.

This article also provides information on the strengths and weaknesses of quantitative and qualitative research. Such information would help researchers appreciate the roles and applications of both research types and how to gain from each or their combination. As different research questions require different types of research and analyses, this article is anticipated to assist researchers better recognize the questions answered by quantitative and qualitative research.

Finally, this article would help researchers to have a balanced perspective of qualitative and quantitative research without considering one as superior to the other.

TYPES OF RESEARCH

Research can be classified into two general types, quantitative and qualitative. 21 Both types of research entail writing a research question and developing a hypothesis. 22 Quantitative research involves a deductive approach to prove or disprove the hypothesis that was developed, whereas qualitative research involves an inductive approach to create a hypothesis. 23 , 24 , 25 , 26

In quantitative research, the hypothesis is stated before testing. In qualitative research, the hypothesis is developed through inductive reasoning based on the data collected. 27 , 28 For types of data and their analysis, qualitative research usually includes data in the form of words instead of numbers more commonly used in quantitative research. 29

Quantitative research usually includes descriptive, correlational, causal-comparative / quasi-experimental, and experimental research. 21 On the other hand, qualitative research usually encompasses historical, ethnographic, meta-analysis, narrative, grounded theory, phenomenology, case study, and field research. 23 , 25 , 28 , 30 A summary of the features, writing approach, and examples of published articles for each type of qualitative and quantitative research is shown in Table 1 . 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43

QUANTITATIVE RESEARCH

Deductive approach.

The deductive approach is used to prove or disprove the hypothesis in quantitative research. 21 , 25 Using this approach, researchers 1) make observations about an unclear or new phenomenon, 2) investigate the current theory surrounding the phenomenon, and 3) hypothesize an explanation for the observations. Afterwards, researchers will 4) predict outcomes based on the hypotheses, 5) formulate a plan to test the prediction, and 6) collect and process the data (or revise the hypothesis if the original hypothesis was false). Finally, researchers will then 7) verify the results, 8) make the final conclusions, and 9) present and disseminate their findings ( Fig. 1A ).

Types of quantitative research

The common types of quantitative research include (a) descriptive, (b) correlational, c) experimental research, and (d) causal-comparative/quasi-experimental. 21

Descriptive research is conducted and written by describing the status of an identified variable to provide systematic information about a phenomenon. A hypothesis is developed and tested after data collection, analysis, and synthesis. This type of research attempts to factually present comparisons and interpretations of findings based on analyses of the characteristics, progression, or relationships of a certain phenomenon by manipulating the employed variables or controlling the involved conditions. 44 Here, the researcher examines, observes, and describes a situation, sample, or variable as it occurs without investigator interference. 31 , 45 To be meaningful, the systematic collection of information requires careful selection of study units by precise measurement of individual variables 21 often expressed as ranges, means, frequencies, and/or percentages. 31 , 45 Descriptive statistical analysis using ANOVA, Student’s t -test, or the Pearson coefficient method has been used to analyze descriptive research data. 46

Correlational research is performed by determining and interpreting the extent of a relationship between two or more variables using statistical data. This involves recognizing data trends and patterns without necessarily proving their causes. The researcher studies only the data, relationships, and distributions of variables in a natural setting, but does not manipulate them. 21 , 45 Afterwards, the researcher establishes reliability and validity, provides converging evidence, describes relationship, and makes predictions. 47

Experimental research is usually referred to as true experimentation. The researcher establishes the cause-effect relationship among a group of variables making up a study using the scientific method or process. This type of research attempts to identify the causal relationships between variables through experiments by arbitrarily controlling the conditions or manipulating the variables used. 44 The scientific manuscript would include an explanation of how the independent variable was manipulated to determine its effects on the dependent variables. The write-up would also describe the random assignments of subjects to experimental treatments. 21

Causal-comparative/quasi-experimental research closely resembles true experimentation but is conducted by establishing the cause-effect relationships among variables. It may also be conducted to establish the cause or consequences of differences that already exist between, or among groups of individuals. 48 This type of research compares outcomes between the intervention groups in which participants are not randomized to their respective interventions because of ethics- or feasibility-related reasons. 49 As in true experiments, the researcher identifies and measures the effects of the independent variable on the dependent variable. However, unlike true experiments, the researchers do not manipulate the independent variable.

In quasi-experimental research, naturally formed or pre-existing groups that are not randomly assigned are used, particularly when an ethical, randomized controlled trial is not feasible or logical. 50 The researcher identifies control groups as those which have been exposed to the treatment variable, and then compares these with the unexposed groups. The causes are determined and described after data analysis, after which conclusions are made. The known and unknown variables that could still affect the outcome are also included. 7

QUALITATIVE RESEARCH

Inductive approach.

Qualitative research involves an inductive approach to develop a hypothesis. 21 , 25 Using this approach, researchers answer research questions and develop new theories, but they do not test hypotheses or previous theories. The researcher seldom examines the effectiveness of an intervention, but rather explores the perceptions, actions, and feelings of participants using interviews, content analysis, observations, or focus groups. 25 , 45 , 51

Distinctive features of qualitative research

Qualitative research seeks to elucidate about the lives of people, including their lived experiences, behaviors, attitudes, beliefs, personality characteristics, emotions, and feelings. 27 , 30 It also explores societal, organizational, and cultural issues. 30 This type of research provides a good story mimicking an adventure which results in a “thick” description that puts readers in the research setting. 52

The qualitative research questions are open-ended, evolving, and non-directional. 26 The research design is usually flexible and iterative, commonly employing purposive sampling. The sample size depends on theoretical saturation, and data is collected using in-depth interviews, focus groups, and observations. 27

In various instances, excellent qualitative research may offer insights that quantitative research cannot. Moreover, qualitative research approaches can describe the ‘lived experience’ perspectives of patients, practitioners, and the public. 53 Interestingly, recent developments have looked into the use of technology in shaping qualitative research protocol development, data collection, and analysis phases. 54

Qualitative research employs various techniques, including conversational and discourse analysis, biographies, interviews, case-studies, oral history, surveys, documentary and archival research, audiovisual analysis, and participant observations. 26

Conducting qualitative research

To conduct qualitative research, investigators 1) identify a general research question, 2) choose the main methods, sites, and subjects, and 3) determine methods of data documentation access to subjects. Researchers also 4) decide on the various aspects for collecting data (e.g., questions, behaviors to observe, issues to look for in documents, how much (number of questions, interviews, or observations), 5) clarify researchers’ roles, and 6) evaluate the study’s ethical implications in terms of confidentiality and sensitivity. Afterwards, researchers 7) collect data until saturation, 8) interpret data by identifying concepts and theories, and 9) revise the research question if necessary and form hypotheses. In the final stages of the research, investigators 10) collect and verify data to address revisions, 11) complete the conceptual and theoretical framework to finalize their findings, and 12) present and disseminate findings ( Fig. 1B ).

Types of qualitative research

The different types of qualitative research include (a) historical research, (b) ethnographic research, (c) meta-analysis, (d) narrative research, (e) grounded theory, (f) phenomenology, (g) case study, and (h) field research. 23 , 25 , 28 , 30

Historical research is conducted by describing past events, problems, issues, and facts. The researcher gathers data from written or oral descriptions of past events and attempts to recreate the past without interpreting the events and their influence on the present. 6 Data is collected using documents, interviews, and surveys. 55 The researcher analyzes these data by describing the development of events and writes the research based on historical reports. 2

Ethnographic research is performed by observing everyday life details as they naturally unfold. 2 It can also be conducted by developing in-depth analytical descriptions of current systems, processes, and phenomena or by understanding the shared beliefs and practices of a particular group or culture. 21 The researcher collects extensive narrative non-numerical data based on many variables over an extended period, in a natural setting within a specific context. To do this, the researcher uses interviews, observations, and active participation. These data are analyzed by describing and interpreting them and developing themes. A detailed report of the interpreted data is then provided. 2 The researcher immerses himself/herself into the study population and describes the actions, behaviors, and events from the perspective of someone involved in the population. 23 As examples of its application, ethnographic research has helped to understand a cultural model of family and community nursing during the coronavirus disease 2019 outbreak. 56 It has also been used to observe the organization of people’s environment in relation to cardiovascular disease management in order to clarify people’s real expectations during follow-up consultations, possibly contributing to the development of innovative solutions in care practices. 57

Meta-analysis is carried out by accumulating experimental and correlational results across independent studies using a statistical method. 21 The report is written by specifying the topic and meta-analysis type. In the write-up, reporting guidelines are followed, which include description of inclusion criteria and key variables, explanation of the systematic search of databases, and details of data extraction. Meta-analysis offers in-depth data gathering and analysis to achieve deeper inner reflection and phenomenon examination. 58

Narrative research is performed by collecting stories for constructing a narrative about an individual’s experiences and the meanings attributed to them by the individual. 9 It aims to hear the voice of individuals through their account or experiences. 17 The researcher usually conducts interviews and analyzes data by storytelling, content review, and theme development. The report is written as an in-depth narration of events or situations focused on the participants. 2 , 59 Narrative research weaves together sequential events from one or two individuals to create a “thick” description of a cohesive story or narrative. 23 It facilitates understanding of individuals’ lives based on their own actions and interpretations. 60

Grounded theory is conducted by engaging in an inductive ground-up or bottom-up strategy of generating a theory from data. 24 The researcher incorporates deductive reasoning when using constant comparisons. Patterns are detected in observations and then a working hypothesis is created which directs the progression of inquiry. The researcher collects data using interviews and questionnaires. These data are analyzed by coding the data, categorizing themes, and describing implications. The research is written as a theory and theoretical models. 2 In the write-up, the researcher describes the data analysis procedure (i.e., theoretical coding used) for developing hypotheses based on what the participants say. 61 As an example, a qualitative approach has been used to understand the process of skill development of a nurse preceptor in clinical teaching. 62 A researcher can also develop a theory using the grounded theory approach to explain the phenomena of interest by observing a population. 23

Phenomenology is carried out by attempting to understand the subjects’ perspectives. This approach is pertinent in social work research where empathy and perspective are keys to success. 21 Phenomenology studies an individual’s lived experience in the world. 63 The researcher collects data by interviews, observations, and surveys. 16 These data are analyzed by describing experiences, examining meanings, and developing themes. The researcher writes the report by contextualizing and reporting the subjects’ experience. This research approach describes and explains an event or phenomenon from the perspective of those who have experienced it. 23 Phenomenology understands the participants’ experiences as conditioned by their worldviews. 52 It is suitable for a deeper understanding of non-measurable aspects related to the meanings and senses attributed by individuals’ lived experiences. 60

Case study is conducted by collecting data through interviews, observations, document content examination, and physical inspections. The researcher analyzes the data through a detailed identification of themes and the development of narratives. The report is written as an in-depth study of possible lessons learned from the case. 2

Field research is performed using a group of methodologies for undertaking qualitative inquiries. The researcher goes directly to the social phenomenon being studied and observes it extensively. In the write-up, the researcher describes the phenomenon under the natural environment over time with no implantation of controls or experimental conditions. 45

DIFFERENCES BETWEEN QUANTITATIVE AND QUALITATIVE RESEARCH

Scientific researchers must be aware of the differences between quantitative and qualitative research in terms of their working mechanisms to better understand their specific applications. This knowledge will be of significant benefit to researchers, especially during the planning process, to ensure that the appropriate type of research is undertaken to fulfill the research aims.

In terms of quantitative research data evaluation, four well-established criteria are used: internal validity, external validity, reliability, and objectivity. 23 The respective correlating concepts in qualitative research data evaluation are credibility, transferability, dependability, and confirmability. 30 Regarding write-up, quantitative research papers are usually shorter than their qualitative counterparts, which allows the latter to pursue a deeper understanding and thus producing the so-called “thick” description. 29

Interestingly, a major characteristic of qualitative research is that the research process is reversible and the research methods can be modified. This is in contrast to quantitative research in which hypothesis setting and testing take place unidirectionally. This means that in qualitative research, the research topic and question may change during literature analysis, and that the theoretical and analytical methods could be altered during data collection. 44

Quantitative research focuses on natural, quantitative, and objective phenomena, whereas qualitative research focuses on social, qualitative, and subjective phenomena. 26 Quantitative research answers the questions “what?” and “when?,” whereas qualitative research answers the questions “why?,” “how?,” and “how come?.” 64

Perhaps the most important distinction between quantitative and qualitative research lies in the nature of the data being investigated and analyzed. Quantitative research focuses on statistical, numerical, and quantitative aspects of phenomena, and employ the same data collection and analysis, whereas qualitative research focuses on the humanistic, descriptive, and qualitative aspects of phenomena. 26 , 28

Structured versus unstructured processes

The aims and types of inquiries determine the difference between quantitative and qualitative research. In quantitative research, statistical data and a structured process are usually employed by the researcher. Quantitative research usually suggests quantities (i.e., numbers). 65 On the other hand, researchers typically use opinions, reasons, verbal statements, and an unstructured process in qualitative research. 63 Qualitative research is more related to quality or kind. 65

In quantitative research, the researcher employs a structured process for collecting quantifiable data. Often, a close-ended questionnaire is used wherein the response categories for each question are designed in which values can be assigned and analyzed quantitatively using a common scale. 66 Quantitative research data is processed consecutively from data management, then data analysis, and finally to data interpretation. Data should be free from errors and missing values. In data management, variables are defined and coded. In data analysis, statistics (e.g., descriptive, inferential) as well as central tendency (i.e., mean, median, mode), spread (standard deviation), and parameter estimation (confidence intervals) measures are used. 67

In qualitative research, the researcher uses an unstructured process for collecting data. These non-statistical data may be in the form of statements, stories, or long explanations. Various responses according to respondents may not be easily quantified using a common scale. 66

Composing a qualitative research paper resembles writing a quantitative research paper. Both papers consist of a title, an abstract, an introduction, objectives, methods, findings, and discussion. However, a qualitative research paper is less regimented than a quantitative research paper. 27

Quantitative research as a deductive hypothesis-testing design

Quantitative research can be considered as a hypothesis-testing design as it involves quantification, statistics, and explanations. It flows from theory to data (i.e., deductive), focuses on objective data, and applies theories to address problems. 45 , 68 It collects numerical or statistical data; answers questions such as how many, how often, how much; uses questionnaires, structured interview schedules, or surveys 55 as data collection tools; analyzes quantitative data in terms of percentages, frequencies, statistical comparisons, graphs, and tables showing statistical values; and reports the final findings in the form of statistical information. 66 It uses variable-based models from individual cases and findings are stated in quantified sentences derived by deductive reasoning. 24

In quantitative research, a phenomenon is investigated in terms of the relationship between an independent variable and a dependent variable which are numerically measurable. The research objective is to statistically test whether the hypothesized relationship is true. 68 Here, the researcher studies what others have performed, examines current theories of the phenomenon being investigated, and then tests hypotheses that emerge from those theories. 4

Quantitative hypothesis-testing research has certain limitations. These limitations include (a) problems with selection of meaningful independent and dependent variables, (b) the inability to reflect subjective experiences as variables since variables are usually defined numerically, and (c) the need to state a hypothesis before the investigation starts. 61

Qualitative research as an inductive hypothesis-generating design

Qualitative research can be considered as a hypothesis-generating design since it involves understanding and descriptions in terms of context. It flows from data to theory (i.e., inductive), focuses on observation, and examines what happens in specific situations with the aim of developing new theories based on the situation. 45 , 68 This type of research (a) collects qualitative data (e.g., ideas, statements, reasons, characteristics, qualities), (b) answers questions such as what, why, and how, (c) uses interviews, observations, or focused-group discussions as data collection tools, (d) analyzes data by discovering patterns of changes, causal relationships, or themes in the data; and (e) reports the final findings as descriptive information. 61 Qualitative research favors case-based models from individual characteristics, and findings are stated using context-dependent existential sentences that are justifiable by inductive reasoning. 24

In qualitative research, texts and interviews are analyzed and interpreted to discover meaningful patterns characteristic of a particular phenomenon. 61 Here, the researcher starts with a set of observations and then moves from particular experiences to a more general set of propositions about those experiences. 4

Qualitative hypothesis-generating research involves collecting interview data from study participants regarding a phenomenon of interest, and then using what they say to develop hypotheses. It involves the process of questioning more than obtaining measurements; it generates hypotheses using theoretical coding. 61 When using large interview teams, the key to promoting high-level qualitative research and cohesion in large team methods and successful research outcomes is the balance between autonomy and collaboration. 69

Qualitative data may also include observed behavior, participant observation, media accounts, and cultural artifacts. 61 Focus group interviews are usually conducted, audiotaped or videotaped, and transcribed. Afterwards, the transcript is analyzed by several researchers.

Qualitative research also involves scientific narratives and the analysis and interpretation of textual or numerical data (or both), mostly from conversations and discussions. Such approach uncovers meaningful patterns that describe a particular phenomenon. 2 Thus, qualitative research requires skills in grasping and contextualizing data, as well as communicating data analysis and results in a scientific manner. The reflective process of the inquiry underscores the strengths of a qualitative research approach. 2

Combination of quantitative and qualitative research

When both quantitative and qualitative research methods are used in the same research, mixed-method research is applied. 25 This combination provides a complete view of the research problem and achieves triangulation to corroborate findings, complementarity to clarify results, expansion to extend the study’s breadth, and explanation to elucidate unexpected results. 29

Moreover, quantitative and qualitative findings are integrated to address the weakness of both research methods 29 , 66 and to have a more comprehensive understanding of the phenomenon spectrum. 66

For data analysis in mixed-method research, real non-quantitized qualitative data and quantitative data must both be analyzed. 70 The data obtained from quantitative analysis can be further expanded and deepened by qualitative analysis. 23

In terms of assessment criteria, Hammersley 71 opined that qualitative and quantitative findings should be judged using the same standards of validity and value-relevance. Both approaches can be mutually supportive. 52

Quantitative and qualitative research must be carefully studied and conducted by scientific researchers to avoid unethical research and inadequate outcomes. Quantitative research involves a deductive process wherein a research question is answered with a hypothesis that describes the relationship between independent and dependent variables, and the testing of the hypothesis. This investigation can be aptly termed as hypothesis-testing research involving the analysis of hypothesis-driven experimental studies resulting in a test of significance. Qualitative research involves an inductive process wherein a research question is explored to generate a hypothesis, which then leads to the development of a theory. This investigation can be aptly termed as hypothesis-generating research. When the whole spectrum of inductive and deductive research approaches is combined using both quantitative and qualitative research methodologies, mixed-method research is applied, and this can facilitate the construction of novel hypotheses, development of theories, or refinement of concepts.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Data curation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Formal analysis: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C.
• Investigation: Barroga E, Matanguihan GJ, Takamiya Y, Izumi M.
• Methodology: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Project administration: Barroga E, Matanguihan GJ.
• Resources: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Supervision: Barroga E.
• Validation: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.
• Visualization: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ, Furuta A, Arima M, Tsuchiya S, Kawahara C, Takamiya Y, Izumi M.

The Penn Libraries has built a new, user-focused library catalog, with a simpler look and easier search features. Explore it at find.library.upenn.edu .

Research and Write Effectively: Dissertation, Thesis, Term paper

Working on a doctoral dissertation, a master's thesis, a senior capstone, or an undergraduate term paper? Meet with a subject librarian to refine your research question, design a literature review search, learn about research methods, and connect to tools for qualitative and quantitative analysis.  

Book a consultation

Consult with a Librarian

Students are invited to meet with their subject librarian to receive help with:

• Refining a research topic
• Accessing guidance about qualitative, quantitative, and mixed methods research design
• Locating collections of primary sources and secondary datasets
• Constructing and documenting a literature search strategy
• Evaluating the credibility of sources
• Learning about software options for gathering, storing, and analyzing data
• Using citation style guides to give credit to sources 

Not sure who to contact? Chat with us online , or request a consultation to be matched with a specialist.

More Services

Looking for more ways to get help with your research? Check out these services.

Identify Resources: Search Skills and Techniques

Read and write critically: information literacy, upcoming events.

Research Basics

Learn fundamental skills for gathering literature relevant to any research project.

• 4:00pm - 5:00pm
• Goldstein Electronic Classroom, Room 114, Van Pelt-Dietrich Library Center

Reference Management Workshop

Learn how to use the popular citation management tool Zotero to keep track of your sources as you research and easily cite sources as you are writing.

• 1:00pm - 2:00pm
• Gershwind & Bennett Family Collaborative Classroom, Holman Biotech Commons

In this workshop, we will walk you through the basics of using Zotero to save and organize sources as well as generate citations. 

• 11:00am - 12:30pm
• Graduate Student Center, 3615 Locust Walk, Third Floor, Room 304
• Get Expert Help
• Undergraduates
• Graduate Students

How To Write Methodology For A Quantitative Study?

Methodology Chapter Provides Information On All The Steps Taken For The Study Of A Problem And The Justifications Given For Specific Steps Taken To Gather, Process, And Analyze Data Related To Understanding The Problem. The Chapter Allows The Reader To Understand And Evaluate The Research Design And Thus Validate It.

Quantitative Study: Quantitative Research Is The Quantification Of A Problem Via Generating Numerical Data That Are Most Often Converted Into Statistics. The Statistical Analysis In Research Methodology Helps In Proving Or Disproving A Thesis. The Research Is Usually Conducted Among A Broad Populace In The Form Of Questionnaire, Polls And Other Surveys Which Involves The Participants To Reply In Numbers. This Means Quantitative Research Falls Under The Headings Of Empirical Or Statistical Studies. Its Main Characteristics Are :

• Use Of Standard Instruments To Gather Data.
• Sizes Of The Samples Are Proportional To That Of The Population In Question.
• Research Is Conducted On A Well-Defined Question.
• Studies Are Well Designed Before The Process.
• Numerical Data That Quantify A Problem Or An Area Of Research Using Various Means Like Charts, Tables, Graphs, Etc. Data Collection Carried Out Through Surveys, Questionnaires, Etc.

A Methodology Chapter For A Quantitative Study Explains The Following In A Direct And Precise Manner:

How Was The Data Generated? How Was It Processed? Why Was The Design, That Was Used, Used?

Any Methodology Chapter Must Be Written In The Past Tense And Follows The Following Guidelines: Chapter Provides Information On The Methods Of Data Collection To Enable The Readers To Understand The Process.

• Significance Of The Methodology Is That A Proper Methodology Validates The Study As A Whole.
• Methodology Section Should Provide A Rationale For Choosing A Particular Design.
• Methods Used Must Be Valid And Conforming To The Conventional Norms Of Research. As Such, The Methodology Chapter Must Provide Enough Evidence To Support The Credibility Of Each Method Used.
• The Appropriateness Of The Methods Chosen Must Be Stated. Only The Methods That Are Appropriate To The Scale Of The Subject In Investigation Must Be Chosen.
• The Chapter Must Contain Information On The Constraints And Challenges That Were Anticipated Before The Beginning Of The Study, The Steps Taken To Prevent The Problems From Occurring, And The Ways The Constraints That Did Occur Were Tackled With Minimal Impact And How The Said Impact Doesn’t Affect The Outcome Of The Study.
• Necessary Information To Replicate Any Particular Method Must Be Provided Concisely In The Chapter.

A methodology for a quantitative study begins with a reiteration of the research question and its context.

This is followed by the research design , where the methods used to gather, process and analyze the data are given. This is usually preceded or followed by a justification of the appropriateness of the research design . Then, the information on the pilot study is given. It is followed by the precise information on sampling strategies, instrument design, and methods of data analysis . ‘ Ethical considerations ’ comes next . Here the researcher informs the reader of the measures taken to ensure participants privacy and consent, etc. Penultimate to concluding the methodology chapter is problems and limitations, where the reader is informed of all the constraints the researcher anticipated and all the problems that occurred and the limitations methods may pose to the overall study.

Links, Related Posts

– indispensable qualitative research methods.

• Qualitative Research Design Methodology
• Quantitative Research Design Methodology
• Research Methodology Help
• Research Methodology Services

• A global market analysis (1)
• Academic (22)
• Algorithms (1)
• Big Data Analytics (4)
• Bio Statistics (3)
• Clinical Prediction Model (1)
• Corporate (9)
• Corporate statistics service (1)
• Data Analyses (23)
• Data collection (11)
• Genomics & Bioinformatics (1)
• Guidelines (2)
• Machine Learning – Blogs (1)
• Network Analysis (1)
• Predictive analyses (2)
• Qualitative (1)
• Quantitaive (2)
• Quantitative Data analysis service (1)
• Research (59)
• Shipping & Logistics (1)
• Statistical analysis service (7)
• Statistical models (1)
• Statistical Report Writing (1)
• Statistical Software (10)
• Statistics (64)
• Survey & Interview from Statswork (1)
• Uncategorized (3)

Recent Posts

• Top 10 Machine Learning Algorithms Expected to Shape the Future of AI
• Data-Driven Governance: Revolutionizing State Youth Policies through Web Scraping
• The Future is Now: The Potential of Predictive Analytics Models and Algorithms
• 2024 Vision: Exploring the Impact and Evolution of Advanced Analytics Tools
• Application of machine learning in marketing

Statswork is a pioneer statistical consulting company providing full assistance to researchers and scholars. Statswork offers expert consulting assistance and enhancing researchers by our distinct statistical process and communication throughout the research process with us.

Functional Area

– Research Planning – Tool Development – Data Mining – Data Collection – Statistics Coursework – Research Methodology – Meta Analysis – Data Analysis

• – Corporate
• – Statistical Software
• – Statistics

Corporate Office

#10, Kutty Street, Nungambakkam, Chennai, Tamil Nadu – 600034, India No : +91 4433182000, UK No : +44-1223926607 , US No : +1-9725029262 Email: [email protected]

Website: www.statswork.com

© 2024 Statswork. All Rights Reserved

We Trust in Human Precision

20,000+ Professional Language Experts Ready to Help. Expertise in a variety of Niches.

API Solutions

• API Pricing
• Cost estimate
• Customer loyalty program
• Educational Discount
• Non-Profit Discount
• Green Initiative Discount1

Value-Driven Pricing

Unmatched expertise at affordable rates tailored for your needs. Our services empower you to boost your productivity.

• Special Discounts
• Enterprise transcription solutions
• Enterprise translation solutions
• Transcription/Caption API
• AI Transcription Proofreading API

Trusted by Global Leaders

GoTranscript is the chosen service for top media organizations, universities, and Fortune 50 companies.

GoTranscript

One of the Largest Online Transcription and Translation Agencies in the World. Founded in 2005.

Speaker 1: In this video, we're going to explain exactly how to write up the results chapter for a quantitative study, whether that's a dissertation, thesis, or any other kind of academic research project. We'll walk you through the process step by step so that you can craft your results section with confidence. So, grab a cup of coffee, grab a cup of tea, whatever works for you, and let's jump into it. Hey, welcome to Grad Coach TV, where we demystify and simplify the oftentimes intimidating world of academic research. My name's Emma, and today we're going to explore the results chapter, which is also sometimes called the findings chapter in a dissertation or thesis. If you're new here, be sure to hit that subscribe button for more videos covering all things research related. Also, if you're looking for hands-on help with your research, check out our one-on-one coaching services, where we help you craft your research project step by step. It's basically like having a friendly professor in your pocket whenever you need it. If that sounds interesting to you, you can learn more and book a free consultation at www.gradcoach.com. All right, with that out of the way, let's get into it. Before we get into the nuts and bolts of how to write up the results chapter, it's useful to take a step back and ask the question, what exactly is a results chapter, and what purpose does it serve? If you understand both the what and the why, you'll have a much clearer direction in terms of the how. So, what's the results chapter all about then? Well, as the name suggests, the results chapter showcases the results of your quantitative analysis. In other words, it presents all the statistical data you've generated in a systematic and intuitive fashion. The results chapter is one of the most important chapters of your dissertation because it shows the reader what you found in terms of the quantitative data you've collected and analyzed. It presents the data using a clear text-based narrative, which is supported by tables, graphs, and charts. In addition to presenting these findings, it also highlights any potential issues you've come across, such as statistical outliers or unusual findings. But how's that different from the discussion chapter, you ask? Well, in the results chapter, you only present your statistical findings. Contrasted to this, in the discussion chapter, you interpret your findings and link them to prior research, in other words, your literature review, as well as your research objectives and research questions. Therefore, the key difference is that in the results chapter, you present and describe the data, while in the discussion chapter, you interpret the data and explain what it means in terms of the bigger picture. Let's take a look at an example. In your results chapter, you may have a plot that shows how respondents to a survey responded to a survey, the number of respondents per category, for instance. You may also state whether this supports one of your hypotheses by using a p-value from a statistical test. In other words, you're just presenting the facts and figures. Contrasted to this, in the discussion chapter, you will say why these statistical findings are relevant to your research question and how they compare with the existing literature. In other words, in the discussion chapter, you'll interpret your findings in relation to your research objectives. Long story short, the results chapter's job is purely to present and describe the data. So keep this in mind and make sure that you don't present anything other than the hard facts and figures. This is not the place for subjective interpretation. Now, a quick caveat. It's worth mentioning that some universities prefer you to combine the results and discussion chapters. Even so, it's still a good idea to separate the results and discussion elements within the chapter, as this ensures your findings are both described and interpreted in a consistent fashion. Typically, though, the results and discussion chapters are split up in quantitative studies. If you're unsure, chat with your research supervisor to find out what their preference is. All right, now that we've got that out of the way, we can look at how to write up the results chapter. Let's do it. There are multiple steps involved in writing up the results chapter for a quantitative study. The exact number of steps will vary from project to project and will depend on the nature of the research aims, objectives, and research questions. For example, some studies will make use of both descriptive and inferential statistics, while others will only use the former. So, in this video, we'll outline a generic process and structure that you can follow, but keep in mind that you may need to trim it down based on your specific research objectives. The first step in crafting your results chapter is to revisit your research objectives and questions. These will be, or at least should be, the driving force behind both your results and discussion chapters. During your statistical analysis, you will have generated a mountain of data, so you need to use your research objectives and questions to sift through this data and decide what's relevant. Therefore, the first step is for you to review your research objectives and research questions very closely and then ask yourself which statistical analyses and tests would specifically help you address these. For each research objective and research question, list the specific piece or pieces of analysis that address it. Keep this list handy as you'll revisit it multiple times as you craft your results chapter. 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. Every point you raise in your discussion chapter will need to be backed up in the results chapter, so you need to make sure that you lay a firm foundation there. So, jot down the main points you want to make in your discussion chapter and then list the specific piece of analysis that addresses each point. Having considered both of these areas, you should now have a short list of potential analyses and data points that you know need to be included in your results chapter in some shape or form. Next, you should draw up a rough outline of how you plan to structure your chapter. This doesn't need to be highly detailed, but you need to think about how you'll order the various analyses in your chapter so that there's a smooth logical flow. We'll discuss the standard structure of a quantitative results chapter in more detail shortly, but it's worth mentioning now that it's essential to draw up a rough outline before you start writing or you'll end up with a wishy-washy mess of information. This advice applies to any chapter, by the way. As with all chapters in your dissertation or thesis, you need to 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 the sample demographic data to understand the composition and representativeness of the sample before moving on to X to understand Y and Z. This introduction section shouldn't be lengthy. A paragraph or two is more than enough. The aim is simply to give the reader a heads up about what you'll cover, not to provide a summary of the findings. Also, it's a good idea to weave the research questions into this section so that there's a golden thread that runs through your document. The first set of data that you'll typically present in your results chapter is an overview of the sample demographics. In other words, you'll give the reader an overview regarding the demographics of your survey respondents. For example, what age groups exist and how are they distributed? How is gender distributed? How is ethnicity distributed? What areas do the participants live in? Why is this important, you ask? Well, the purpose of this section is to assess how representative the sample is of the broader population. This is important for the sake of generalizability of the results. If your sample is not representative of the population, you won't be able to generalize your findings. This isn't necessarily a bad thing, but it's a limitation you'll need to acknowledge. Of course, to make this representativeness assessment, you'll need to already have an understanding of the demographics of the actual population you're interested in. 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 generalizability, you say? Well, even if you don't intend 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, the demographic data will help you contextualize your findings accurately. For example, if 80% of your sample was aged over 65, this may be a noteworthy contextual factor to consider when interpreting the data. Similarly, if a large portion of your sample was skewed towards one gender, this would be an important contextual factor to note. Long story short, regardless of your intention to produce generalizable results, it's essential to understand and clearly communicate the demographic data of your sample. So, be sure to put in the time and effort in this section so that you can contextualize your findings accurately. Before you undertake your core statistical analysis, you 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 analyze data that doesn't meet the assumptions of a specific statistical method or technique, your results will be largely meaningless. Therefore, you need to do some checks on your data before you jump into the actual analysis. Most commonly, there are two areas you need to pay attention to. The first thing you need to check is the reliability of your composite measures. 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 scales that all aim to measure the same thing, but are phrased in different ways. In other words, within a survey, these four scales should all receive similar ratings, assuming they are indeed measuring the same thing. This is called internal consistency. Unfortunately, internal consistency is not guaranteed, especially if you developed the scales yourself. So, you need to assess the reliability of each composite measure using a test. Cronbach's alpha is a common test used to assess internal consistency. In other words, to show that the items you're combining are more or less saying the same thing. A high alpha score means that your composite measure is internally consistent. A low alpha score means you may need to scrap one or more of the individual measures. There are tests other than Cronbach's alpha that can be used, and there's some hot debate about which one is the best, but we won't get into that here. The key takeaway is that you need to undertake some sort of testing to assess internal consistency, and you need to present those test results in this section of your chapter. Once you're comfortable that your composite measures are internally consistent, the next thing you need to look at is the shape of the data for each of your variables. What do you mean the shape of the data? Well, for each variable, you need to assess whether the data are symmetrical. In other words, normally distributed in a nice bell curve or not. This is important as it will directly impact what type of analysis methods and techniques you can use. For many common inferential tests, such as t-test and ANOVAs, we'll discuss these a bit later, don't stress, your data needs to be normally distributed. In other words, symmetrical. If it's not, you'll need to adjust your strategy and use alternative statistical tests. To assess the shape of the data, you'll usually assess a variety of fairly basic descriptive statistics, such as the mean, median, and skewness, which is exactly what we'll look at next. Now that you've laid the foundation by examining the representativeness of your sample, the reliability of your composite measures, and the shape of your data, you can get started with the actual statistical analysis. Finally. The first step is to present the descriptive statistics for your variables. As I mentioned, the descriptive statistics will help you assess the shape of your data. As I mentioned, the descriptive statistics will help you assess the shape of your data. But depending on the nature of your research, the descriptive statistics could also play an important role in directly addressing your research objectives and research questions. So, what are descriptive statistics? When we talk about descriptives, this usually includes basic 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. 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? Or do they lean to the left or the right? And lastly, 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. If these statistics sound like gibberish to you, be sure to check out our video covering the basics of quantitative data analysis. I'll include the link below. When you're presenting your descriptive stats, using a large table to present all the stats for multiple variables can be a very effective way to present your data economically. This saves you a lot of space and makes it easier to compare and contrast the statistics for each variable. You can also use color coding to help make the data more easily digestible. For categorical data, for example, data that shows the percentage of people who chose or fit into each category, you can either just plain describe the percentages or numbers of people who responded to something, or you could use graphs and charts such as bar graphs and pie charts to present your data. There's no one size fits all approach here. In some cases, it will make more sense to just present the numbers in a table or a paragraph. For example, if there are only two categories. While in other cases, graphs and charts will be useful. For example, if there are multiple categories. A pro tip, when using charts and graphs, make sure that you label them simply and clearly so that your reader can easily understand them. There is nothing more frustrating than a graph that's missing axis labels. Keep in mind that although you'll be presenting tables, 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 point. Highlight the crucial trends and values in the body of the text. Figures and tables should complement your writing, not carry it. All right, so that covers the basics of descriptive statistics. Depending on your research aims, objectives and research questions, you may end your analysis here. However, if your study also requires inferential statistics, then it's time to get started on those. All right, on to inferentials. Unlike descriptive statistics where the focus is purely on the sample, inferential statistics are used to make predictions about the population. So this part of the results chapter is where things can get really interesting. Inferential methods, broadly speaking, can be broken up into two groups. First up, there are those analyses that compare measurements between groups, such as t-tests, which measure differences between two groups, and ANOVAs, which measure differences between multiple groups. For example, you could use ANOVA to assess the difference in average weight loss between three groups that adopted three different diets. The second type of inferential methods are those that assess relationships between variables, such as correlation analysis and regression analysis. For example, you could use correlation analysis to assess the relationship between the number of hours studied and test marks earned within a sample of students. Within each of these inferentials, some tests can be used for normally distributed data, in other words, symmetrical data. And some tests are designed specifically for use on non-normally distributed data. So it's important to make sure that you use the right analysis tool for your data shape. Remember, you would have assessed data shape in your descriptive statistics section, so make sure that you align your inferential approach with those findings. There are a seemingly endless number of analysis methods and 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. Therefore, you need to be selective about which methods you use. Ultimately, the most important thing is to make sure that you adopt the analysis methods that allow you to achieve your research objectives and answer your research questions. So let those two factors guide you. As with the descriptive statistics, in this section of your results chapter, you should try to make use of figures and tables as effectively as possible. For example, if you present a correlation table, use color coding to highlight the significance of the correlation values, or present a scatter plot 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. Right. With both your descriptive and inferential statistics presented, you should have now laid the foundation for your discussion chapter. So at this stage, it's a good idea to quickly revisit that list that you drew up in step one and make sure you've covered all the necessary data to support your research objectives and research questions. If you have, you're ready to take the next step. If your study requires it, the next component of your results chapter will be hypothesis testing. Not every study will need hypotheses, so don't feel like you need to shoehorn these in if you haven't got any. As with so many things in your dissertation, the need for hypotheses depends on your research aims, objectives, and questions. So what exactly is a hypothesis? Generally speaking, a hypothesis is a statement that expresses an expected difference between groups or a relationship between variables. Importantly, it's a statement that can be supported or rejected by a statistical test. In other words, it needs to be very specific and measurable and cannot leave any room for interpretation or subjectivity. For example, a statement like, there is a relationship between study hours and test marks scored could be supported or rejected by a statistical test. For example, correlation analysis. Contrasted to this, a statement like, ice cream is the meaning of life, couldn't be supported by a statistical test, as much as I wish it could be. So if your dissertation or thesis included the development of hypotheses in the literature review chapter, this section is where you'd present them once again and test them using your statistical data. If you want to learn more about hypotheses, check out our detailed post over on the Grad Coach blog. I'll include a link below this video. One last thing. If your research involved developing a theoretical framework, you can, at this stage, present that framework once again, this time populating it with the hypothesis testing data. For example, if you were developing a theoretical model of the antecedents of trust and your hypotheses related to the antecedent variables, you could present the model again, this time incorporating the test results for each variable. Right, with your quantitative analyses presented, it's time to wrap up your results chapter and transition to the discussion chapter. To conclude your results chapter, the final step is to provide a brief summary of the key findings. Brief is the key word here. Much like the chapter introduction, this shouldn't be lengthy, a paragraph or two maximum. In this section, you only need to highlight the findings most relevant to your research objectives and research questions so that you lay the foundation for the next chapter. Don't provide a lengthy recap of each and every section of results. Just remind the reader of the key takeaways and wrap it up. If you work through your results chapter step-by-step as we've discussed in this video, you should land up with a comprehensive presentation of your key data. Keep in mind that what we've discussed here is a generic structure. There's no one-size-fits-all. The exact structure and contents of your results chapter will be influenced by your specific research objectives and research questions. As I mentioned in step one, start by crafting a list that covers your research objectives and questions and mapping that to the various statistical analyses and tests you've undertaken. Revisit that list as you work through each section of your results chapter and you can rest assured that you'll be headed in a good direction. All right, so that wraps it up for today. If you enjoyed the video, hit the like button and please leave a comment if you have any questions. Also, be sure to subscribe for more research-related content. Remember, if you need a helping hand with your research, be sure to check out our private coaching service where we work with you on a one-on-one basis, chapter-by-chapter, to help you craft a winning dissertation, thesis, or research project. If that sounds interesting to you, book a free consultation with a friendly coach at www.gradcoach.com. As always, I'll include a link below. That's all for this episode of Grad Coach TV. Until next time, good luck. Grad Coach

Recommended pages

• New staff intranet
• Student Welcome
• Online registration
• MyUoB mobile app
• Campus maps
• Lecture timetables
• Study spaces
• Student digital services
• Student support
• Student printing
• Car parking
• Room bookings
• Core systems
• Staff development

Presenting your thesis

 formatting your thesis.

Please refer to Regulation 7.4.2 for important information on how to format your thesis.

The Library Services guide 'Presenting your thesis' has been written as the standard for all theses presented for research degrees in the University of Birmingham. 

It offers guidance on the practicalities of producing your thesis in a format that is acceptable for examination and for deposit in the library. This guide does not deal with the content and academic standard required of a thesis and on these matters you are advised to consult University Regulations, your supervisor and guidance issued by your School.

Please also see the  Getting your thesis ready workshop webpage .

 Thesis word limit

On submitting your thesis for examination you are required to complete a declaration form confirming the word length of your thesis. You should therefore be aware of the maximum word length for your thesis. See  Regulation 7.4.2 (d).

The stated maximum number of words excludes tables, diagrams (including associated legends), appendices, list of references, footnotes and endnotes, the bibliography and any bound published material. For information on referencing styles see the  iCite – referencing at the University of Birmingham  webpages.

A thesis that exceeds the maximum number of words will not be accepted for examination unless permission to exceed the stated word count has been granted by the Research Progress & Awards Sub Panel. Permission to exceed the stated word count is only granted in exceptional circumstances. If you consider that you will not be able to meet the stated word limited, you are advised to discuss this with your supervisor at an early stage.

 Language of your thesis

 acknowledging collaborative work.

If any material is included in your thesis which is a result of collaborative working, you must include details of how much of the work is your own and how much is that of other people. See Regulation 7.4.1 (h).

It is also important to seek the prior agreement of those other people to make your thesis available in the University eTheses Repository. 

 Previously published or submitted work

You may include work that has already been published providing the work is properly integrated, either in the thesis or as an appendix to which reference is made - see  Regulation 7.4.1 (g). It must be adequately referenced and you are advised to consult with your supervisor if you are unsure about the inclusion of any previously published work in your thesis. 

For additional information please refer to the Copyright for Researchers web page

You may not include material for assessment which has already been submitted for another degree awarded at this or any other University, unless all of the conditions set out in Regulation 7.4.1 (f) are satisfied.

If you are considering including published papers in your thesis, please read the alternative format thesis guide (Word - 22KB).

 Plagiarism

Plagiarism is a form of cheating and is a serious academic offence. It arises where work submitted is not the student's own and has been taken from another source. The original material is then hidden from the marker, either by not referencing it properly, by paraphrasing it or by not mentioning it at all.

For further information see the University’s Guidance on plagiarism for students .

All theses submitted for examination are checked through plagiarism detection software.

 Editorial help for PGR theses

A thesis submitted for examination at the University of Birmingham must be solely the postgraduate researcher’s own work (except where University Regulations permit the inclusion of appropriately referenced collaborative research or work – see Regulation 7.4.1 . A postgraduate researcher must not employ a ‘ghost writer’ to write parts or all of the thesis, whether in draft or as a final version, on his/her behalf.

Editors, whether they are formal supervisors, informal mentors, family or friends or professional, need to be clear about the extent and nature of help they offer in the editing of University of Birmingham PGRs theses and dissertations. Supervisors of PGRs also need to be clear about the role of the third party editors as well as their own editorial role.

PGRs may use third party editorial assistance (paid or voluntary) from an outside source.  This must be with the knowledge and support of supervisors and the use of third party editorial assistance must be stated in the thesis acknowledgement page.

A ‘third party’ editor cannot be used :

• To change the text of the thesis so as to clarify and/or develop the ideas and arguments;
• To reduce the length of the thesis so it falls within the specified word limit;
• To correct information within the thesis;
• To change ideas and arguments put forward within the thesis; and/or
• To translate the thesis into English.

A ‘third party’ editor can be used to offer advice on:

• Spelling and punctuation;
• Formatting and sorting of footnotes and endnotes for consistency and order;
• Ensuring the thesis follows the conventions of grammar and syntax in written English;
• Shortening long sentences and editing long paragraphs;
• Changing passives and impersonal usages into actives, vice versa as may be appropriate;
• Improving the positioning of tables and illustrations and the clarity, grammar, spelling and punctuation of any text in or under tables and illustrations; and
• Ensuring consistency of page numbers, headers and footers.

Where a third party editor is used it is the PGR’s responsibility to provide the third party editor with a copy of this statement (Word - 20KB)  and ensure they complete the Third Party Editor Declaration Form (Word - 32KB)  confirming their compliance with this statement.

When submitting the thesis the PGR must record in the Acknowledgements page the form of contribution the ‘third party’ editor has made, by stating for example, “this thesis was copy edited for conventions of language, spelling and grammar by ABC Editing Ltd”.

Please also see the Code of Practice on Academic Integrity .

 Intellectual property rights

These rights generally belong to the student, but if your work is considered to be commercially significant students may be required to assign their rights to the University. 

For further information please see:

• University Regulation 5.4 covering Intellectual Property
• Regulation 3.16 covering Patents and The Exploitation of Inventions
• The Copyright for Researchers webpage

 Can't find what you're looking for?

• College of Arts and Law
• College of Engineering and Physical Sciences
• College of Life and Environmental Sciences
• College of Medicine and Health
• College of Social Sciences

Professional Services

• Academic Services
• Campus Services
• Development and Alumni Relations
• Executive Support
• External Relations
• Human Resources
• IT Services
• Legal Services
• Research Strategy and Services

• The Student Experience
• Financial Aid
• Degree Finder
• Undergraduate Arts & Sciences
• Departments and Programs
• Research, Scholarship & Creativity
• Centers & Institutes
• Geisel School of Medicine
• Guarini School of Graduate & Advanced Studies
• Thayer School of Engineering
• Tuck School of Business

Campus Life

• Diversity & Inclusion
• Athletics & Recreation
• Student Groups & Activities
• Residential Life

Quantitative Social Science

Program in quantitative social science.

• [email protected] Contact & Department Info Mail
• Undergraduate
• What is it like to write a QSS thesis?
• Questions about the curriculum
• What is it like to complete a one quarter QSS research project?
• What can I do with a QSS degree?
• Wisdom from alumni
• Course Schedule by Term
• QSS student prize
• Class of 2024
• Class of 2023
• Class of 2022
• Class of 2021
• Class of 2020
• Class of 2019
• Class of 2018
• Selected theses 2022-23
• Selected theses 2021-22
• Selected theses 2020-21
• Selected theses 2019-20
• Selected theses 2018-19
• Selected theses 2017-18
• Selected theses 2016-17
• Selected theses 2015-16
• Selected 2018-19 Projects
• Selected 2017-18 projects
• Selected 2016-17 projects
• Faculty-Student Collaborations
• About the Program
• General questions
• Questions about research
• Student perspectives on QSS
• News & Events
• News & Events
• Dartmouth Interdisciplinary Network Research Group
• Past Events
• Faculty, Fellows, Affiliates & Staff
• Alumni Stories
• Tell Us Your Story

Search form

Introducing jack andolina, a new addition to dartmouth's program in quantitative social science.

The Program in Quantitative Social Science ( QSS ) at  Dartmouth College  is excited to welcome Jack Andolina, an accomplished researcher with a passion for computational social science, to our academic community.

Academic Background and Research Expertise

Jack completed his B.S. in Political Science and Data Analytics at  UC San Diego  in June 2024, where he excelled both academically and in research. His senior thesis, titled "Quantifying Partisan Media Bias: Gatekeeping and Framing of Congressional Misconduct," was awarded high honors under the mentorship of  Dr. Umberto Mignozzetti . This work highlights Jack's ability to delve deeply into complex issues at the intersection of media and politics, using data-driven approaches to uncover insights into how media bias influences public perception.

Before joining Dartmouth, Jack served as the Computational Social Science Research Lead at the  Institute of Cyber Archaeology and Sustainability  within the  Qualcomm Institute . There, he honed his skills in applied artificial intelligence and led projects that bridged technology and social science. Jack's work has been recognized at conferences, including the  American Society of Overseas Research  and the  Pi Sigma Alpha Political Science  conferences, where he presented his research on AI applications and partisan media bias.

Professional Experience

In addition to his academic achievements, Jack brings a wealth of professional experience to Dartmouth.  As the Computer Social Science & Team Leader at the Center for Cyber-Archeology and Sustainability, Qualcomm Institute, he led a team of interdisciplinary undergraduates in creating a digital twin of Chula Vista's Bayfront District, Hollywood's Vinyl District, and UC San Diego. At U.S. News & World Report, Jack served as a Product Analyst Intern, where he developed a web scraper to collect extensive government data and efficiently cleaned and processed large datasets using Python. Additionally, as the Executive Legislative Intern at the County of San Diego, Jack engineered essential data infrastructure, utilizing innovative VBA scripts and conducting comprehensive data analysis, which facilitated seamless engagement with 620,000 constituents.These experiences have equipped him with a broad perspective on how data can be leveraged to inform policy and media practices.

Role at Dartmouth

At Dartmouth, Jack will be taking on the role of a post-baccalaureate Research Associate in Quantitative Social Science. Working closely with Professor  Brendan Nyhan , member of the QSS Steering Committee and James O. Freedman Presidential Professor of Government, and Professor  John Carey , a QSS affiliate and John Wentworth Professor in the Social Sciences and Government, Jack's primary focus will be Bright Line Watch , which surveys the state of democracy in the United States. Jack will be involved in many aspects of this project, from survey design to the analysis of results, contributing to a deeper understanding of the challenges facing democracy today. In addition to his work on Bright Line Watch, Jack will be engaged in several other research initiatives. He will contribute to a social media misinformation project focused on understanding the dynamics of misinformation spread on social platforms, though details of this work will be restricted by a non-disclosure agreement (NDA).

Personal Interests

Outside of his professional and academic pursuits, Jack enjoys exploring the arts and the outdoors.. Jack enjoys writing music, hiking, painting, and participating in a variety of outdoor activities.

QSS is thrilled to have Jack Andolina join Dartmouth, and we look forward to the innovative research and fresh perspectives he will bring to QSS.