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How To Write The Results/Findings Chapter

For quantitative studies (dissertations & theses).

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

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

Overview: Quantitative Results Chapter

  • What exactly the results chapter is
  • What you need to include in your chapter
  • How to structure the chapter
  • Tips and tricks for writing a top-notch chapter
  • Free results chapter template

What exactly is the results chapter?

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

But how’s that different from the discussion chapter?

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

Let’s look at an example.

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

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

Free template for results section of a dissertation or thesis

What should you include in the results chapter?

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

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

How do I decide what’s relevant?

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

There must be alignment between your research aims objectives and questions

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

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

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

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

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

Need a helping hand?

analysis chapter in thesis

How do I write the results chapter?

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

Step 1 – Revisit your research questions

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

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

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

Step 2 – Craft an overview introduction

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

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

Your chapter must have a golden thread

Step 3 – Present the sample demographic data

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

For example:

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

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

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

But what if I’m not interested in generalisability?

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

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

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

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

#1: Composite measures

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

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

#2: Data shape

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

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

Descriptive statistics

Step 5 – Present the descriptive statistics

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

For scaled data, this usually includes statistics such as:

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

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

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

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

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

Dive into the inferential statistics

Step 6 – Present the inferential statistics

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

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

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

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

make it easy for your reader to understand your quantitative results

Step 7 – Test your hypotheses

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

The basic process for hypothesis testing is as follows:

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

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

Step 8 – Provide a chapter summary

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

Some final thoughts, tips and tricks

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

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

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

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How to write the results chapter in a qualitative thesis

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

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Awesome content 👏🏾

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this was great explaination

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Writing the Data Analysis Chapter(s): Results and Evidence

Posted by Rene Tetzner | Oct 19, 2021 | PhD Success | 0 |

Writing the Data Analysis Chapter(s): Results and Evidence

4.4 Writing the Data Analysis Chapter(s): Results and Evidence

Unlike the introduction, literature review and methodology chapter(s), your results chapter(s) will need to be written for the first time as you draft your thesis even if you submitted a proposal, though this part of your thesis will certainly build upon the preceding chapters. You should have carefully recorded and collected the data (test results, participant responses, computer print outs, observations, transcriptions, notes of various kinds etc.) from your research as you conducted it, so now is the time to review, organise and analyse the data. If your study is quantitative in nature, make sure that you know what all the numbers mean and that you consider them in direct relation to the topic, problem or phenomenon you are investigating, and especially in relation to your research questions and hypotheses. You may find that you require the services of a statistician to help make sense of the data, in which case, obtaining that help sooner rather than later is advisable, because you need to understand your results thoroughly before you can write about them. If, on the other hand, your study is qualitative, you will need to read through the data you have collected several times to become familiar with them both as a whole and in detail so that you can establish important themes, patterns and categories. Remember that ‘qualitative analysis is a creative process and requires thoughtful judgments about what is significant and meaningful in the data’ (Roberts, 2010, p.174; see also Miles & Huberman, 1994) – judgements that often need to be made before the findings can be effectively analysed and presented. If you are combining methodologies in your research, you will also need to consider relationships between the results obtained from the different methods, integrating all the data you have obtained and discovering how the results of one approach support or correlate with the results of another. Ideally, you will have taken careful notes recording your initial thoughts and analyses about the sources you consulted and the results and evidence provided by particular methods and instruments as you put them into practice (as suggested in Sections 2.1.2 and 2.1.4), as these will prove helpful while you consider how best to present your results in your thesis.

Although the ways in which to present and organise the results of doctoral research differ markedly depending on the nature of the study and its findings, as on author and committee preferences and university and department guidelines, there are several basic principles that apply to virtually all theses. First and foremost is the need to present the results of your research both clearly and concisely, and in as objective and factual a manner as possible. There will be time and space to elaborate and interpret your results and speculate on their significance and implications in the final discussion chapter(s) of your thesis, but, generally speaking, such reflection on the meaning of the results should be entirely separate from the factual report of your research findings. There are exceptions, of course, and some candidates, supervisors and departments may prefer the factual presentation and interpretive discussion of results to be blended, just as some thesis topics may demand such treatment, but this is rare and best avoided unless there are persuasive reasons to avoid separating the facts from your thoughts about them. If you do find that you need to blend facts and interpretation in reporting your results, make sure that your language leaves no doubt about the line between the two: words such as ‘seems,’ ‘appears,’ ‘may,’ ‘might,’ probably’ and the like will effectively distinguish analytical speculation from more factual reporting (see also Section 4.5).

analysis chapter in thesis

You need not dedicate much space in this part of the thesis to the methods you used to arrive at your results because these have already been described in your methodology chapter(s), but they can certainly be revisited briefly to clarify or lend structure to your report. Results are most often presented in a straightforward narrative form which is often supplemented by tables and perhaps by figures such as graphs, charts and maps. An effective approach is to decide immediately which information would be best included in tables and figures, and then to prepare those tables and figures before you begin writing the text for the chapter (see Section 4.4.1 on designing effective tables and figures). Arranging your data into the visually immediate formats provided by tables and figures can, for one, produce interesting surprises by enabling you to see trends and details that you may not have noticed previously, and writing the report of your results will prove easier when you have the tables and figures to work with just as your readers ultimately will. In addition, while the text of the results chapter(s) should certainly highlight the most notable data included in tables and figures, it is essential not to repeat information unnecessarily, so writing with the tables and figures already constructed will help you keep repetition to a minimum. Finally, writing about the tables and figures you create will help you test their clarity and effectiveness for your readers, and you can make any necessary adjustments to the tables and figures as you work. Be sure to refer to each table and figure by number in your text and to make it absolutely clear what you want your readers to see or understand in the table or figure (e.g., ‘see Table 1 for the scores’ and ‘Figure 2 shows this relationship’).

analysis chapter in thesis

Beyond combining textual narration with the data presented in tables and figures, you will need to organise your report of the results in a manner best suited to the material. You may choose to arrange the presentation of your results chronologically or in a hierarchical order that represents their importance; you might subdivide your results into sections (or separate chapters if there is a great deal of information to accommodate) focussing on the findings of different kinds of methodology (quantitative versus qualitative, for instance) or of different tests, trials, surveys, reviews, case studies and so on; or you may want to create sections (or chapters) focussing on specific themes, patterns or categories or on your research questions and/or hypotheses. The last approach allows you to cluster results that relate to a particular question or hypothesis into a single section and can be particularly useful because it provides cohesion for the thesis as a whole and forces you to focus closely on the issues central to the topic, problem or phenomenon you are investigating. You will, for instance, be able to refer back to the questions and hypotheses presented in your introduction (see Section 3.1), to answer the questions and confirm or dismiss the hypotheses and to anticipate in relation to those questions and hypotheses the discussion and interpretation of your findings that will appear in the next part of the thesis (see Section 4.5). Less effective is an approach that organises the presentation of results according to the items of a survey or questionnaire, because these lend the structure of the instrument used to the results instead of connecting those results directly to the aims, themes and argument of your thesis, but such an organisation can certainly be an important early step in your analysis of the findings and might even be valid for the final thesis if, for instance, your work focuses on developing the instrument involved.

analysis chapter in thesis

The results generated by doctoral research are unique, and this book cannot hope to outline all the possible approaches for presenting the data and analyses that constitute research results, but it is essential that you devote considerable thought and special care to the way in which you structure the report of your results (Section 6.1 on headings may prove helpful). Whatever structure you choose should accurately reflect the nature of your results and highlight their most important and interesting trends, and it should also effectively allow you (in the next part of the thesis) to discuss and speculate upon your findings in ways that will test the premises of your study, work well in the overall argument of your thesis and lead to significant implications for your research. Regardless of how you organise the main body of your results chapter(s), however, you should include a final paragraph (or more than one paragraph if necessary) that briefly summarises and explains the key results and also guides the reader on to the discussion and interpretation of those results in the following chapter(s).

Why PhD Success?

To Graduate Successfully

This article is part of a book called "PhD Success" which focuses on the writing process of a phd thesis, with its aim being to provide sound practices and principles for reporting and formatting in text the methods, results and discussion of even the most innovative and unique research in ways that are clear, correct, professional and persuasive.

analysis chapter in thesis

The assumption of the book is that the doctoral candidate reading it is both eager to write and more than capable of doing so, but nonetheless requires information and guidance on exactly what he or she should be writing and how best to approach the task. The basic components of a doctoral thesis are outlined and described, as are the elements of complete and accurate scholarly references, and detailed descriptions of writing practices are clarified through the use of numerous examples.

analysis chapter in thesis

The basic components of a doctoral thesis are outlined and described, as are the elements of complete and accurate scholarly references, and detailed descriptions of writing practices are clarified through the use of numerous examples. PhD Success provides guidance for students familiar with English and the procedures of English universities, but it also acknowledges that many theses in the English language are now written by candidates whose first language is not English, so it carefully explains the scholarly styles, conventions and standards expected of a successful doctoral thesis in the English language.

analysis chapter in thesis

Individual chapters of this book address reflective and critical writing early in the thesis process; working successfully with thesis supervisors and benefiting from commentary and criticism; drafting and revising effective thesis chapters and developing an academic or scientific argument; writing and formatting a thesis in clear and correct scholarly English; citing, quoting and documenting sources thoroughly and accurately; and preparing for and excelling in thesis meetings and examinations. 

analysis chapter in thesis

Completing a doctoral thesis successfully requires long and penetrating thought, intellectual rigour and creativity, original research and sound methods (whether established or innovative), precision in recording detail and a wide-ranging thoroughness, as much perseverance and mental toughness as insight and brilliance, and, no matter how many helpful writing guides are consulted, a great deal of hard work over a significant period of time. Writing a thesis can be an enjoyable as well as a challenging experience, however, and even if it is not always so, the personal and professional rewards of achieving such an enormous goal are considerable, as all doctoral candidates no doubt realise, and will last a great deal longer than any problems that may be encountered during the process.

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Rene Tetzner

Rene Tetzner's blog posts dedicated to academic writing. Although the focus is on How To Write a Doctoral Thesis, many other important aspects of research-based writing, editing and publishing are addressed in helpful detail.

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Dissertations 5: findings, analysis and discussion: home.

  • Results/Findings

Alternative Structures

The time has come to show and discuss the findings of your research. How to structure this part of your dissertation? 

Dissertations can have different structures, as you can see in the dissertation  structure  guide.

Dissertations organised by sections

Many dissertations are organised by sections. In this case, we suggest three options. Note that, if within your course you have been instructed to use a specific structure, you should do that. Also note that sometimes there is considerable freedom on the structure, so you can come up with other structures too. 

A) More common for scientific dissertations and quantitative methods:

- Results chapter 

- Discussion chapter

Example: 

  • Introduction
  • Literature review
  • Methodology
  • (Recommendations)

if you write a scientific dissertation, or anyway using quantitative methods, you will have some  objective  results that you will present in the Results chapter. You will then interpret the results in the Discussion chapter.  

B) More common for qualitative methods

- Analysis chapter. This can have more descriptive/thematic subheadings.

- Discussion chapter. This can have more descriptive/thematic subheadings.

  • Case study of Company X (fashion brand) environmental strategies 
  • Successful elements
  • Lessons learnt
  • Criticisms of Company X environmental strategies 
  • Possible alternatives

C) More common for qualitative methods

- Analysis and discussion chapter. This can have more descriptive/thematic titles.

  • Case study of Company X (fashion brand) environmental strategies 

If your dissertation uses qualitative methods, it is harder to identify and report objective data. Instead, it may be more productive and meaningful to present the findings in the same sections where you also analyse, and possibly discuss, them. You will probably have different sections dealing with different themes. The different themes can be subheadings of the Analysis and Discussion (together or separate) chapter(s). 

Thematic dissertations

If the structure of your dissertation is thematic ,  you will have several chapters analysing and discussing the issues raised by your research. The chapters will have descriptive/thematic titles. 

  • Background on the conflict in Yemen (2004-present day)
  • Classification of the conflict in international law  
  • International law violations
  • Options for enforcement of international law
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  • Bartek Buczkowski   ORCID: orcid.org/0000-0002-4146-3664 4  

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The Discussion chapter brings an opportunity to write an academic argument that contains a detailed critical evaluation and analysis of your research findings. This chapter addresses the purpose and critical nature of the discussion, contains a guide to selecting key results to discuss, and details how best to structure the discussion with subsections and paragraphs. We also present a list of points to do and avoid when writing the discussion together with a Discussion chapter checklist.

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Braun V, Clarke V (2013) Successful qualitative research: a practical guide for beginners. SAGE Publications, London

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PLOS (2023) Author resources. How to write discussions and conclusions. Accessed Mar 3, 2023, from https://plos.org/resource/how-to-write-conclusions/ . Accessed 3 Mar 2023

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Cottrell S (2017) Critical thinking skills: effective analysis, argument and reflection, 3rd edn. Palgrave, London

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Reeves, S., Buczkowski, B. (2023). How Do I Write the Discussion Chapter?. In: Mastering Your Dissertation. Springer, Cham. https://doi.org/10.1007/978-3-031-41911-9_9

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How to Write a Dissertation Discussion Chapter – A Quick Guide with Examples

Published by Alvin Nicolas at August 12th, 2021 , Revised On September 20, 2023

Dissertation discussion is the chapter where you explore the relevance, significance, and meanings of your findings  – allowing you to showcase your talents in describing and analyzing the results of your study.

Here, you will be expected to demonstrate how your research findings  answer the  research questions  established or test the  hypothesis .

The arguments you assert in the dissertation analysis and discussions chapter lay the foundations of your conclusion . It is critically important to discuss the results in a precise manner.

To help you understand how to write a dissertation discussion chapter, here is the list of the main elements of this section so you stay on the right track when writing:

  • Summary: Start by providing a summary of your key research findings
  • Interpretations: What is the significance of your findings?
  • Implications: Why are your findings important to academic and scientific communities, and what purpose would they serve?
  • Limitations: When and where will your results have no implications?
  • Future Recommendations : Advice for other researchers and scientists who explore the topic further in future.

The dissertation discussion chapter should be carefully drafted to ensure that the results mentioned in your research align with your research question, aims, and objectives.

Considering the importance of this chapter for all students working on their dissertations, we have comprehensive guidelines on how to write a dissertation discussion chapter.

The discussion and  conclusion  chapters often overlap. Depending on your university, you may be asked to group these two sections in one chapter – Discussion and Conclusion.

In some cases, the results and discussion are put together under the Results and Discussion chapter. Here are some dissertation examples of working out the best structure for your dissertation.

Alternatively, you can look for the required  dissertation structure in your handbook  or consult your supervisor.

Steps of How to Write Dissertation Discussion Chapter

1. provide a summary of your findings.

Start your discussion by summarising the key findings of your research questions. Avoid repeating the information you have already stated in the previous chapters.

You will be expected to clearly express your interpretation of results to answer the research questions established initially in one or two paragraphs.

Here are some  examples of how to present the summary of your findings ;

  • “The data suggests that”,
  • “The results confirm that”,
  • “The analysis indicates that”,
  • “The research shows a relationship between”, etc.

2. Interpretations of Results

Your audience will expect you to provide meanings of the results, although they might seem obvious to you. The results and their interpretations should be linked to the research questions so the reader can understand the value your research has added to the literature.

There are many ways of interpreting the data, but your chosen approach to interpreting the data will depend on the  type of research involved . Some of the most common strategies employed include;

  • Describing how and why you ended up with unexpected findings and explaining their importance in detail
  • Relating your findings with previous studies conducted
  • Explaining your position with logical arguments when/if any alternative explanations are suggested
  • An in-depth discussion around whether or not the findings answered your research questions and successfully tested the hypothesis

Examples of how you can start your interpretation in the Discussion chapter are –

  • “Findings of this study contradict those of Allen et al. (2014) that”,
  • “Contrary to the hypothesized association,” “Confirming the hypothesis…”,
  • “The findings confirm that A is….. even though Allen et al. (2014) and Michael (2012) suggested B was …..”

3. Implications of your Study

What practical and theoretical implications will your study have for other researchers and the scientific community as a whole?

It is vital to relate your results to the knowledge in the existing literature so the readers can establish how your research will contribute to the existing data.

When thinking of the possible consequences of your findings, you should ask yourself these;

  • Are your findings in line with previous studies? What contribution did your research make to them?
  • Why are your results entirely different from other studies on the same topic?
  • Did your findings approve or contradict existing knowledge?
  • What are the practical implications of your study?

Remember that as the researcher, you should aim to let your readers know why your study will contribute to the existing literature. Possible ways of starting this particular section are;

  • “The findings show that A….. whereas Lee (2017) and John (2013) suggested that B”, “The results of this study completely contradict the claims made in theories”,
  • “These results are not in line with the theoretical perspectives”,
  • “The statistical analysis provides a new understanding of the relationship between A and B”,
  • “Future studies should take into consideration the findings of this study because”

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4. Recognise the Limitations of your Research

Almost every academic research has some limitations. Acknowledging them will only add to your credibility as a scientific researcher.

In addition to the possible human errors, it’s important to take into account other factors that might have influenced the results of your study, including but not limited to unexpected research obstacles, specific methodological choices , and the overall research design.

Avoid mentioning any limitations that may not be relevant to your research aim, but clearly state the limitations that may have affected your results.

For example, if you used a sample size that included a tiny population, you may not generalise your results.

Similarly, obstacles faced in collecting data from the participants can influence the findings of your study. Make a note of all such  research limitations , but explain to the reader why your results are still authentic.

  • The small sample size limited the generalisability of the results.
  • The authenticity of the findings may have been influenced by….
  • The obstacles in collecting data resulted in…
  • It is beyond the framework of this research…

5. Provide Recommendations for Future Research

The limitations of your research work directly result in future recommendations. However, it should be noted that your recommendations for future research work should include the areas that your own work could not report so other researchers can build on them.

Sometimes the recommendations are a part of the  conclusion chapter . Some examples;

  • More research is needed to be performed….

Image result for research limitations

The Purpose of Dissertation Discussion Chapter 

Remember that the discussion section of a dissertation is the heart of your research because a) it will indicate your stance on the topic of research, and b) it answers the research questions initially established in the Introduction chapter .

Every piece of information you present here will add value to the existing literature within your field of study. How you structured your findings in the preceding chapter will help you determine the best structure for your dissertation discussion section.

For example, it might be logical to structure your analysis/discussions by theme if you chose the pattern in your findings section.

But generally, discussion based on research questions is the more widely used  structure  in academia because this pattern clearly indicates how you have addressed the aim of your research.

Most UK universities require the supervisor or committee members to comment on the extent to which each research question has been answered. You will be doing them a great favour if you structure your discussion so that each research question is laid out separately.

Irrespective of whether you are  writing an essay, dissertation, or  chapter of a dissertation , all pieces of writing should start with an  introduction .

Once your readers have read through your study results, you might want to highlight the contents of the subsequent discussion as an introduction paragraph (summary of your results – as explained above).

Likewise, the discussion chapter is expected to end with a concluding paragraph – allowing you the opportunity to summarise your interpretations.

The dissertation analysis & discussion chapter is usually very long, so it will make sense to emphasise the critical points in a concluding paragraph so the reader can grasp the essential information. This will also help to make sure the reader understands your analysis.

Also Read:   Research Discussion Of Findings

Useful Tips 

Presentation of graphs, tables, and figures.

In the 1990s and early 2000s, students spent days creating graphs and charts for their  statistical analysis work . Thanks to technology, you can produce even more accurate graphs and figures today in a shorter period.

Using  Microsoft Word, STATA, SPSS, Microsoft Excel  and other statistical analysis software, we can now draw  beautiful-looking figures, tables , and graphs with just a few clicks and make them appear in our document at the desired place. But there are downsides to being too dependent on technology.

Many students make the common mistake of using colours to represent variables when really they have to print their dissertation paper final copy in black and white.

Any colours on graphs and figures will eventually be viewed in the grayscale presentation. Recognizing different shades of grey on the same chart or graph can sometimes be a little confusing.

For example, green and purple appear as pretty much the same shade of grey on a line chat, meaning your chart will become unreadable to the marker.

Another trap you may fall into is the unintentional stuffing   of the dissertation chapter with graphs and figures. Even though it is essential to show numbers and statistics, you don’t want to overwhelm your readers with too many.

It may not be necessary to have a graph/table under each sub-heading. Only you can best judge whether or not you need to have a graph/table under a particular sub-heading as the writer.

Image result for excel graphs and charts

Relating to Previous Chapters  

As a student, it can be challenging to develop your own analysis and discussion of results. One of the excellent discussion chapter requirements is to showcase your ability to relate previous research to your research results.

Avoid repeating the same information over and over. Many students fall into this trap which negatively affects the mark of their overall dissertation paper .

Concise and to-the-point information will help you effectively convey your point to the readers.

Although you must demonstrate how your findings relate to previous research, it is equally important to ensure you are not simply rewriting what has already been said in the introduction  and  literature review  chapters.

The best strategy is to use examples from previous sections to postulate an argument.

Hyperlinks are recommended to take the reader from one section to another. This is especially important for submitting electronic documents as .word or .pdf files. Hyperlinking is tedious and time-consuming, so you should allow for this in your dissertation timeline to avoid rushing in the closing stages.

Also read: How to Write the Abstract for the Dissertation.

Using Subsections and Subheadings

You might want to reflect on the structure of the discussion in your organizstion of the dissertation discussion chapter, and for that, you will need to create sub-sections.

It is essential to keep subsections to the point and as short as possible. Use a layer of subheadings if possible.

For example

Subsection 4.1 of Chapter 4- Discussion can be further divided into sections 4.1.1 and 4.2.2. After three numerical layers (4.1.1, 4.2.2, and 4.2.3), any subheadings need not appear in the contents table.

The titles of all subsections will appear on your table of contents  so choose the wordings carefully. A title too long or too short might confuse the reader. A one or two-word subheading will not give the reader enough information to understand the section.

Likewise, using a research question or long sentences in the subheading is not recommended. It might help to examine how other researchers and writers create these subheadings.

Critical Thinking

Your critical thinking skills are the crux of your dissertation discussion chapter. You will do yourself a great disservice if you fail to put the critical thinking element into the equation.

After all, this exercise aims to showcase clarity in your thoughts and arguments. Markers of the dissertation give more importance to the analysis  and discussion chapter. But you could be marked negatively if this particular chapter lacks critical thinking.

Many students struggle to distinguish between fundamental descriptive analysis and critical thinking with their opinions on the research topic.

Critical thinking is a skill developed over time, and it might be daunting for you to come to terms with the idea of critical thinking and its use in your analysis. But even if you are no expert, you must try your best.

Image result for critical thinking

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Duplication of Content

Another critical error students make reaffirming the point the graph/chart was supposed to make. Writing out the same information as presented in the graph defeats the whole purpose of having them in the first place.

You will be expected to form your opinions and arguments based on the findings (as presented by the graphs), so keep an eye on this mistake. Finally, avoid simply inserting a graph without any explanation whatsoever.

It should be noted that there is no correct or incorrect number of charts/figures one can use in the dissertation findings and discussion chapter. A balance must be struck.

Avoid Over Interpretation

This is a major no-no when writing a dissertation discussion. Do not make an argument that isn’t backed by your collected data.

The results and interpretations that cannot be supported should not be mentioned. Your research will be deemed unauthentic and will also be questioned by your supervisor if you do so. Results should be interpreted without any bias.

How to Write the Findings of a Dissertation.

Do not Speculate

Speculation in the  discussion chapter of your dissertation is discouraged. Your dissertation’s discussion is based on your collected data and how it relates to your research questions. Thus, speculating here will undoubtedly undermine your research’s credibility.

Also, try not to generalise your findings. If your research is based on a specific population, do not state that the same findings might apply in every case. As indicated previously, it is essential to acknowledge the limitations of your research.

On the other hand, if you think your discussion needs to address other populations as well, start your sentence like this ‘We speculate that..’ or ‘It is speculated that..’ This will keep you from getting into any trouble.

What are the elements of the Dissertation Discussion?

The list of the main elements of the discussion chapter are:

  • Implications : Why are your findings important to academic and scientific communities, and what purpose would they serve?
  • Future Recommendations: Advice for other researchers and scientists who explore the topic further in future.

What are the steps of writing a Dissertation Discussion Chapter?

  • Write a summary of the findings
  • Provide a summary of your findings
  • Interpretations of Results
  • Recognise the Limitations of your research
  • Provide Recommendations for Future Research.

Can we use graphs and charts in the Dissertation Discussion Chapter?

Yes, using graphs to aid your statistical results and enhance presentation is essential, but do not overwhelm it with a lot of graphs in multiple colours. 

You May Also Like

Anyone who supports you in your research should be acknowledged in dissertation acknowledgments. Learn more on how to write dissertation acknowledgements.

A literature review is a survey of theses, articles, books and other academic sources. Here are guidelines on how to write dissertation literature review.

Not sure how to write dissertation title page? All dissertations must have a dissertation title page where necessary information should be clearly presented

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While it is more common for Science, Technology, Engineering and Mathematics (STEM) researchers to write separate, distinct chapters for their data/ results and analysis/ discussion , the same sections can feel less clearly defined for a researcher in Social Sciences, Arts and Humanities (SSAH). This article will look specifically at some useful approaches to writing the analysis and discussion chapters in qualitative/SSAH research.

Note : Most of the differences in approaches to research, writing, analysis and discussion come down, ultimately, to differences in epistemology – how we approach, create and work with knowledge in our respective fields. However, this is a vast topic that deserves a separate discussion.

Look for emerging themes and patterns

The ‘results’ of qualitative research can sometimes be harder to pinpoint than in quantitative research. You’re not dealing with definitive numbers and results in the same way as, say, a scientist conducting experiments that produce measurable data. Instead, most qualitative researchers explore prominent, interesting themes and patterns emerging from their data – that could comprise interviews, textual material or participant observation, for example. 

You may find that your data presents a huge number of themes, issues and topics, all of which you might find equally significant and interesting. In fact, you might find yourself overwhelmed by the many directions that your research could take, depending on which themes you choose to study in further depth. You may even discover issues and patterns that you had not expected , that may necessitate having to change or expand the research focus you initially started off with.

It is crucial at this point not to panic. Instead, try to enjoy the many possibilities that your data is offering you. It can be useful to remind yourself at each stage of exactly what you are trying to find out through this research.

What exactly do you want to know? What knowledge do you want to generate and share within your field?

Then, spend some time reflecting upon each of the themes that seem most interesting and significant, and consider whether they are immediately relevant to your main, overarching research objectives and goals.

Suggestion: Don’t worry too much about structure and flow at the early stages of writing your discussion . It would be a more valuable use of your time to fully explore the themes and issues arising from your data first, while also reading widely alongside your writing (more on this below). As you work more intimately with the data and develop your ideas, the overarching narrative and connections between those ideas will begin to emerge. Trust that you’ll be able to draw those links and craft the structure organically as you write.

Let your data guide you

A key characteristic of qualitative research is that the researchers allow their data to ‘speak’ and guide their research and their writing. Instead of insisting too strongly upon the prominence of specific themes and issues and imposing their opinions and beliefs upon the data, a good qualitative researcher ‘listens’ to what the data has to tell them.

Again, you might find yourself having to address unexpected issues or your data may reveal things that seem completely contradictory to the ideas and theories you have worked with so far. Although this might seem worrying, discovering these unexpected new elements can actually make your research much richer and more interesting. 

Suggestion: Allow yourself to follow those leads and ask new questions as you work through your data. These new directions could help you to answer your research questions in more depth and with greater complexity; or they could even open up other avenues for further study, either in this or future research.

Work closely with the literature

As you analyse and discuss the prominent themes, arguments and findings arising from your data, it is very helpful to maintain a regular and consistent reading practice alongside your writing. Return to the literature that you’ve already been reading so far or begin to check out new texts, studies and theories that might be more appropriate for working with any new ideas and themes arising from your data.

Reading and incorporating relevant literature into your writing as you work through your analysis and discussion will help you to consistently contextualise your research within the larger body of knowledge. It will be easier to stay focused on what you are trying to say through your research if you can simultaneously show what has already been said on the subject and how your research and data supports, challenges or extends those debates. By drawing from existing literature , you are setting up a dialogue between your research and prior work, and highlighting what this research has to add to the conversation.

Suggestion : Although it might sometimes feel tedious to have to blend others’ writing in with yours, this is ultimately the best way to showcase the specialness of your own data, findings and research . Remember that it is more difficult to highlight the significance and relevance of your original work without first showing how that work fits into or responds to existing studies. 

In conclusion

The discussion chapters form the heart of your thesis and this is where your unique contribution comes to the forefront. This is where your data takes centre-stage and where you get to showcase your original arguments, perspectives and knowledge. To do this effectively needs you to explore the original themes and issues arising from and within the data, while simultaneously contextualising these findings within the larger, existing body of knowledge of your specialising field. By striking this balance, you prove the two most important qualities of excellent qualitative research : keen awareness of your field and a firm understanding of your place in it.

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How to Write Discussion Part of Thesis

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January 13 2021 11:07 AM

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How to Write a Discussion (Analysis) Chapter in a Thesis

Discussion and analysis are probably the most critical components of any thesis. These are also the longest sections of your thesis, which require thoroughness, conciseness, attention to detail, brevity, and extensive use of primary and secondary evidence.

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Useful Tips on Writing Correct Thesis Discussion

The article below will help students learn about proper thesis discussion   writing. We will provide you with major objectives and professional approaches to writing. After that, you will have an opportunity to learn about certain steps that can be taken to write a brilliant dissertation discussion chapter.

Objectives and Approaches Writing a Discussion Chapter

Remember the major objectives When writing a dissertation or thesis discussion chapter. You should state your interpretations, declare your point of view, explain the effects of the research findings, and predict and suggest future research work.

Remember that dissertation or thesis discussion   chapter is perceived as the most crucial part of one's work. That is why it is normal for students to cope with this chapter, not for the first time.

Useful Steps for Writing Effective Discussion

It should be precise and short to ensure this chapter is easy to understand. However, the discussion chapter should also state, elaborate, support, provide an explanation and even defend all your logical conclusions. Remember that your writing should not simply repeat the results. It should be a commentary. Do not write about any distracting issues. They will only confuse the reader and hide your message's importance. It is difficult to create a perfect piece of writing, but you should try to make your readers distinguish between facts and speculation.

Follow the below-provided steps, and you will cope with your thesis or dissertation successfully:

  • The structure of the discussion chapter should start with specific information and end with general information. It would be best to slowly transition from some narrow confines to the general facts about the selected discipline.
  • Write the introduction in a general tone. Using the same main terms, viewpoint, and tense in the introductory paragraphs is easy. 
  • You can also rewrite the research questions and restate the hypothesis presented in the introduction. After that, you can provide the answers to the major research questions. Remember that answers should be supported by the research findings.
  • Explain the relationship between your results and the expectations of the study and course literature. Please explain why the obtained results can be accepted and how they fit with existing knowledge about the selected subject. Use correct and relevant citations here. 
  • Pay close attention to the obtained results related to the posed research questions. It does not matter whether the findings were statistically important.  
  • Inform your targeted audience about the principles, patterns, and major relationships detected in your findings, and collect them into one perspective. This information should be sequential. First, give the answer, provide the results, and then cite reliable and academic sources. You can point readers to graphs and figures to enhance the main argument.   
  • All your answers should be defended. You can do this in two ways: explain the validity of the answers and present the other answers' shortcomings. By presenting both sides of the argument, you can strengthen your viewpoint.
  • The conflicting data should be identified in your work as well. Discuss and assess any explanations that conflict with your results. It can help to win with your targeted audience and make them feel sympathetic to the knowledge offered by your study. 
  • Discuss any findings that are perceived as unexpected. Please start with the paragraph related to the finding and provide its description. Identify any potential weaknesses and limitations present in your study. Comment on the significance of the described limitations to your findings and their interpretation. Explain how they can influence their validity. This section cannot have an apologetic tone. Remember that every study has its limitations and weaknesses.    
  • It would be best to summarize the findings' main implications (this should be done regardless of statistical importance) and make a few recommendations regarding any further research. 
  • You should prove the significance of the study results and their conclusions and describe how they can influence our comprehension of the discussed issue(s).  
  • Finally, it would be best to be specific but brief when discussing everything related to the study.

Now you know how to write a discussion paper. We hope that our article inspired you to start writing your paper. You can always find a dissertation discussion example and see its structure.

You cannot write a great thesis   without using a large body of literature. Every claim you make must be supported with credible and verifiable information. The data you provide in these sections will either support or nullify your hypotheses or assumptions. In either case, these results will inform the direction of future research activities.

Consider the requirements for your thesis and ask your thesis supervisor for more detail if you are unsure how much space your discussion and analysis chapter must take. Begin the section with the strongest evidence supporting or refuting your thesis. If you have any doubts, ask for help, and we will be happy to provide sufficient evidence to support your  conclusions .

While working on your project's analysis and discussion chapters, we will adhere to the rules and requirements provided by your supervisor. We will consider the terms and technical vocabulary that must be used in the body of your thesis. We try not to overload discussions with too many technical words so your readers can understand your conclusions.

Otherwise, we will include a glossary of terms to explain the meaning of the most complicated words. You will not have trouble submitting a perfect thesis on time with our writers!

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How To Write The Results/Findings Chapter

For quantitative graduate (dissertations & theses).

By: Derek Johansen (MBA). Accomplished Reviewed The: Kerryn Warren (PhD) | July 2021

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

An outcomes & analysis section in a dissertation

Summary: Quantitative Results Chapter

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

What exactly is the results chapter?

The results chapter (also referred to as the findings or analysis chapter) shall one of the most important chapters of your dissertation or thesis because it exhibitions the reader what you’ve found in terms of the quantitative data you’ve collected. It presents the date using ampere clear write narrative, supported the charts, diagram and charts. In doing so, it also climax any potential issues (such as irregularities button unusual findings) you’ve come across.

Although how’s that different from to discussion chapter?

Well, by the results chapter, you only present your statistical findings. Only the numbers, so to address – no more, no less. Contrasts to this, in the panel chapters , you interpret your findings and linked yours to prior research (i.e. your literature review), as well as your search objectives also research questions. Stylish other words, the results chapter presents both describes the data, while this discussion chapter interprets the data.

Let’s look at an example.

In your result chapter, you maybe have a design is shows how respondents to a survey  responded: to numbers of respondents per category, for instance. You may other state whether this supports a hypothesis by after a p-value from an statistical exam. Aber it is only in an discussion chapter where you will say why this is relevant or how it compares with which literature or the broader picture. So, in your results chapter, induce certainly that her don’t present anything other than the hard facts – is is not the place in subjectivity.

It’s merit mentioning that some universities prefer you to combine the results or discussion click. Even so, it is goody practical to separate the results and discussion elements within the chapter, as this guarantee choose outcome are fully portrayed. Normal, though, the results and discussion books are split boost in quantitative studies. If you’re unsure, chats with your research supervisor or chair to find out what their preference is.

The results and discussion chapter live typically split

What should to include in one results section?

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

Like doesn’t mean that those analyses was a waste out date – on the contrary, who analyses ensure so they have a good understating the your dataset plus how to schauspieler it. However, that doesn’t mean your reader or researcher needs to see the 165 histograms you created! Relevance is key. Data analysis write-ups

How do I decide what’s relevant?

At this point, it may be difficult to strike a balance between what will and isn’t important. But the bulk important things is to ensure your earnings reflect and orient with the purpose of your study .  Like, you need to revisit your choose aims, objectives and search questions plus use these as a litmus test with relevance. Take sure that you refer back to these constantly while print up your chapter so that you stay on pisten.

There must breathe alignment between yours research aims goal and questions

As a general guided, your results book will usually include the following:

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

We’ll explore each off these points in more detailed within the next section.

Importantly, your ergebnisse chapter needed to lay the foundation for your discussion chapter . This means that, in your results chapter, you need to include all the date is she will use more the basis forward your interpretation in who discussion chapter.

For example, if you draft to set the strong relationship between Variable X and Variable UNKNOWN in your discussion chapter, you need to present the respective analysis in your results chapter – perhaps a compare or regressive analysis.

Needing a helping hand?

analysis chapter in thesis

How execute I write the results chapter?

There are repeatedly steps complicated in writing up who results chapter for owner quantitative research. The exact number of steps applicable toward you will vary from study to investigate and will depend on the nature of the research aims, objectives and research questions . However, we’ll outlines the generic stepping below.

Step 1 – Revisit your choose questions

The first step in writing autochthonous results chapter is to revisit your research objectives additionally research questions . Dieser will been (or at least, should be!) the driving forces behind your results and discussion chapters, to you need to review them and then ask your which statistical tests and tests (from choose mountain for data) would specifically help you address these . For each research objective and exploring go, list the specific part (or pieces) of analysis that address it.

At this stage, it’s also useful to thinks about the key points that her want to raise in your topic chapter press note diesen down so this you can a clear reminder of which data points and analyses you what to highlight int the results chapter. Again, list your points and following list the specific piece of analysis that addresses either point.  The analysis chapter is one of the most important spare of a thesis. Here is a finish guide to dissertation data analysis!

Next, you should pull up a rough outline of method you plan to structure your chapter . Which analyses and statistical tests will you present and in about order? We’ll discussed the “standard structure” in more detail later, not it’s worth mentioning now this it’s always useful to tie up a crude outline before you start writing (this advice applies to any chapter).

Speed 2 – Craft any overview introduction

As with all chapters in thy dissertation or dissertation, you should start your quantitative resultat chapter by providing a brief overview of get you’ll do in the chapters and wherefore . For example, you’d explain that thee will start by presenting statistical intelligence into understand the representativeness of the sample, before moving onto X, Y furthermore Z.

This section shouldn’t be lengthy – a paragraph instead two maximum. Also, it’s a good idea to web the research questions on this section so that there’s a glitter thread that runs trough the documents.

Your chapter must have adenine golden thread

Step 3 – Present one sample demographic dating

The first selected of data that you’ll presence is an overview of the sample demographics – includes other words, the census of your respondents.

In example:

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

The purpose of aforementioned is to assess how spokesperson the sample is of and broader population. This is major required the sake of and generalisability of this results. If your sample is not representative of the population, you will not be able to generalise your findings. Which is not necessarily of end of the world, but a is a limitation you’ll need into acknowledge.

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

But get if I’m not interested in generalisability?

Okay, even if your purpose is not necessarily until extend autochthonous findings to the broader population, understanding your sample will allow you until ausleger is findings suitably, considering who reply. On other words, is will help you contextualise is findings . For example, are 80% the your sample was senior over 65, this may be a significant contextual factor to consider at interpreting the data. Therefore, it’s essential toward understand and present the demographic file.

Communicate the data

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

Before you undertake any statistical analysis, you’ll need to do some inspection to ensure that will details be suitable for the analysis processes also techniques you set toward use. If you try to analyse intelligence ensure doesn’t meet the conjectures a a specific statistical technique, own results will be largely meaningless. Therefore, you may need to show that the processes and abilities you’ll getting are “allowed”.

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

#1: Composition measures

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

Internal consistency is not guaranteed though (especially if you developed the measures yourself), so you need until assess the vertrauen of each composed evaluate by a exam. Typically, Cronbach’s Alpha is a joint check used to assess user consistency – i.e., to shows ensure the product you’re combing are more or less sayings the same thing. ONE height alpha score means that your take is internally consistent. ADENINE low alpha score means you may need to consider scrapping one or find of the measures.

#2: Product shape

The second mattigkeit that you should address early go in your results chapter is data shapes. In other words, you need to assess whether the data at insert set are symmetry (i.e. normally distributed) or not, as this will directly impact what type starting analyses you can use. For loads common inferential testing such than T-tests or ANOVAs (we’ll discuss above-mentioned a bit later), your data needed to is normally distributed. If it’s not, you’ll need into adjust your strategy and use alternative tests.

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

Descriptive statistics

Step 5 – Present the descriptive vital

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

By scaled data, this usually includes statistics such as:

  • The mean – this is merely the mathematical average of a range of numbers.
  • The median – like is who midpoint in a range of numbers at the numbers are arranged in order.
  • Aforementioned run – this is who highest commonly repeated number in the file set.
  • Standard variance – this metric indicates how dispersed a range of numbering is. In other words, how close all that numbers can to the mean (the average).
  • Skewness – this indicates how symmetrical a range of numbers is. In other words, do it tend to clustering into a smooth bell curve shaped in the median of the graph (this is calls a normal or parametric distribution), either do they lean to the left or right (this is called a non-normal instead non-parametric distribution).
  • Kurtosis – this metric points whether the data belong heavily or lightly-tailed, relative to the normal dissemination. In other words, how peaked or flat the distribution is.

A bigger table that indicates all to above for repeated variables can be a very effective way to present thy data economically. It can also use colour coding to help make the product more easily digestible.

For categorical data, location you show the percentage of people who chose or perfect into a choose, for instance, it bottle either simply plain describe this percentages or numbers of people who responded to something or usage graphs additionally schedules (such as bar graphs and pie charts) into present your details in this section by the chapter.

When using numbers, produce sure that you label their single and clear , so that your reader can easily understand them. There’s nothing more frustrating than a graph that’s missing axis labels! Keep in mind that although you’ll be presenting charts and graphs, your theme content needs to present an clear narrative that can stand on seine own. By other words, don’t rely purely on insert numbers and tables to convey your main points: highlight the crucial trends and values in the text. Figures and tables have complement who writing, not portable itp .

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

Dive into this inferential statistics

Step 6 – Present the inferential statistischen

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

First, there are those that comparing measurements with bunches , create as t-tests (which measure differences between two groups) and ANOVAs (which gauge discrepancies between multiple groups). Second, there are techniques that assess the relationships between variables , such as correlation analysis and regression analyzed. Within each of these, certain tests can be previously for normally distributed (parametric) data and certain tests are planned specifically for uses on non-parametric data.

Thither are a seemingly endless number of tests that you ability use to crunch your data, so it’s easily go run down a rabbit hole and end up to piles of test data. Ultimately, the most important thing belongs to create sure that you adopt the tests and techniques that authorize it to realisieren your research objectives and answer your research questions .

In this section in the results chapter, you should try to doing use of figures and visual equipment as effectively as possible. For real, if you presenting a relationship charts, use colour encryption to bright the significance of the correlation principles, or scatterplots to optically demonstrate where the trend remains. The light you make it for your reader to digest your findings, the more effectively you’ll will able to make your arguments in the next chapter.

making items easy for your reader to understand your quantitative results

Level 7 – Test your research

If your study requires it, the upcoming stage is hypothesis test. A hypothesis is a statement , often indicating a gauge between groups or relationship between variables, that can becoming supported or rejected by a statistiken test. However, don see studies will involve conjectures (again, it depends on the investigate objectives), so don’t feelings like you “must” present and test hypotheses just because you’re undertaking quantitive research.

Of basic process for hypothesis testing is because follows:

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

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

Step 8 – Offer a chapter summarized

For wrap up your results chapter and transition to the discussion chapter, you should provide a brief summary of an key findings . “Brief” is the keyword her – much like the chapter preamble, this shouldn’t be extensive – a paragraph instead second maximum. Stress the find most relevant to your research objectives and research frequently, and wrap it up.

Needed a helping hand-held?

Some final my, tip and tricks.

Now that you’ve got the essentials downhill, here are a few tips and trick to perform respective quantify results chapter brilliance:

  • Available writing your results chapter, report get what in the past tense . You’re talking around what you’ve found in choose data, not what you are currently find for or trying to find.
  • Structure your results chapter systematically both sequentially . Supposing you must two experiments where findings from which one generated inputs into the other, submit on them at command.
  • Make your own tables and graphs rather than copied press pasting them from static analysis software like SPSS. Checking out the DataIsBeautiful reddit for several inspiration.
  • Once you’re done writing, review thy work to make sure that you had provided enough information to answer your research matter , but additionally that them didn’t include superfluous information.

If you’ve got any questions about writing up the quantitative scores chapter, please walk a commenting below. If you’d like 1-on-1 helps with your quantitative analysis and topic, check out the hands-on coaching service , or book ampere free consultation with a friendly coach.

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How to Write an Impressive Thesis Results Section

analysis chapter in thesis

After collecting and analyzing your research data, it’s time to write the results section. This article explains how to write and organize the thesis results section, the differences in reporting qualitative and quantitative data, the differences in the thesis results section across different fields, and the best practices for tables and figures.

What is the thesis results section?

The thesis results section factually and concisely describes what was observed and measured during the study but does not interpret the findings. It presents the findings in a logical order.

What should the thesis results section include?

  • Include all relevant results as text, tables, or figures
  • Report the results of subject recruitment and data collection
  • For qualitative research, present the data from all statistical analyses, whether or not the results are significant
  • For quantitative research, present the data by coding or categorizing themes and topics
  • Present all secondary findings (e.g., subgroup analyses)
  • Include all results, even if they do not fit in with your assumptions or support your hypothesis

What should the thesis results section not include?

  • If the study involves the thematic analysis of an interview, don’t include complete transcripts of all interviews. Instead, add these as appendices
  • Don’t present raw data. These may be included in appendices
  • Don’t include background information (this should be in the introduction section )
  • Don’t speculate on the meaning of results that do not support your hypothesis. This will be addressed later in the discussion and conclusion sections.
  • Don’t repeat results that have been presented in tables and figures. Only highlight the pertinent points or elaborate on specific aspects

How should the thesis results section be organized?

The opening paragraph of the thesis results section should briefly restate the thesis question. Then, present the results objectively as text, figures, or tables.

Quantitative research presents the results from experiments and  statistical tests , usually in the form of tables and figures (graphs, diagrams, and images), with any pertinent findings emphasized in the text. The results are structured around the thesis question. Demographic data are usually presented first in this section.

For each statistical test used, the following information must be mentioned:

  • The type of analysis used (e.g., Mann–Whitney U test or multiple regression analysis)
  • A concise summary of each result, including  descriptive statistics   (e.g., means, medians, and modes) and  inferential statistics   (e.g., correlation, regression, and  p  values) and whether the results are significant
  • Any trends or differences identified through comparisons
  • How the findings relate to your research and if they support or contradict your hypothesis

Qualitative research   presents results around key themes or topics identified from your data analysis and explains how these themes evolved. The data are usually presented as text because it is hard to present the findings as figures.

For each theme presented, describe:

  • General trends or patterns observed
  • Significant or representative responses
  • Relevant quotations from your study subjects

Relevant characteristics about your study subjects

Differences among the results section in different fields of research

Nevertheless, results should be presented logically across all disciplines and reflect the thesis question and any hypotheses that were tested.

The presentation of results varies considerably across disciplines. For example, a thesis documenting how a particular population interprets a specific event and a thesis investigating customer service may both have collected data using interviews and analyzed it using similar methods. Still, the presentation of the results will vastly differ because they are answering different thesis questions. A science thesis may have used experiments to generate data, and these would be presented differently again, probably involving statistics. Nevertheless, results should be presented logically across all disciplines and reflect the thesis question and any  hypotheses that were tested.

Differences between reporting thesis results in the Sciences and the Humanities and Social Sciences (HSS) domains

In the Sciences domain (qualitative and experimental research), the results and discussion sections are considered separate entities, and the results from experiments and statistical tests are presented. In the HSS domain (qualitative research), the results and discussion sections may be combined.

There are two approaches to presenting results in the HSS field:

  • If you want to highlight important findings, first present a synopsis of the results and then explain the key findings.
  • If you have multiple results of equal significance, present one result and explain it. Then present another result and explain that, and so on. Conclude with an overall synopsis.

Best practices for using tables and figures

The use of figures and tables is highly encouraged because they provide a standalone overview of the research findings that are much easier to understand than wading through dry text mentioning one result after another. The text in the results section should not repeat the information presented in figures and tables. Instead, it should focus on the pertinent findings or elaborate on specific points.

Some popular software programs that can be used for the analysis and presentation of statistical data include  Statistical Package for the Social Sciences (SPSS ) ,  R software ,  MATLAB , Microsoft Excel,  Statistical Analysis Software (SAS) ,  GraphPad Prism , and  Minitab .

The easiest way to construct tables is to use the  Table function in Microsoft Word . Microsoft Excel can also be used; however, Word is the easier option.

General guidelines for figures and tables

  • Figures and tables must be interpretable independent from the text
  • Number tables and figures consecutively (in separate lists) in the order in which they are mentioned in the text
  • All tables and figures must be cited in the text
  • Provide clear, descriptive titles for all figures and tables
  • Include a legend to concisely describe what is presented in the figure or table

Figure guidelines

  • Label figures so that the reader can easily understand what is being shown
  • Use a consistent font type and font size for all labels in figure panels
  • All abbreviations used in the figure artwork should be defined in the figure legend

Table guidelines

  • All table columns should have a heading abbreviation used in tables should be defined in the table footnotes
  • All numbers and text presented in tables must correlate with the data presented in the manuscript body

Quantitative results example : Figure 3 presents the characteristics of unemployed subjects and their rate of criminal convictions. A statistically significant association was observed between unemployed people <20 years old, the male sex, and no household income.

analysis chapter in thesis

Qualitative results example: Table 5 shows the themes identified during the face-to-face interviews about the application that we developed to anonymously report corruption in the workplace. There was positive feedback on the app layout and ease of use. Concerns that emerged from the interviews included breaches of confidentiality and the inability to report incidents because of unstable cellphone network coverage.

Table 5. Themes and selected quotes from the evaluation of our app designed to anonymously report workplace corruption.

Tips for writing the thesis results section

  • Do not state that a difference was present between the two groups unless this can be supported by a significant  p-value .
  • Present the findings only . Do not comment or speculate on their interpretation.
  • Every result included  must have a corresponding method in the methods section. Conversely, all methods  must have associated results presented in the results section.
  • Do not explain commonly used methods. Instead, cite a reference.
  • Be consistent with the units of measurement used in your thesis study. If you start with kg, then use the same unit all throughout your thesis. Also, be consistent with the capitalization of units of measurement. For example, use either “ml” or “mL” for milliliters, but not both.
  • Never manipulate measurement outcomes, even if the result is unexpected. Remain objective.

Results vs. discussion vs. conclusion

Results are presented in three sections of your thesis: the results, discussion, and conclusion.

  • In the results section, the data are presented simply and objectively. No speculation or interpretation is given.
  • In the discussion section, the meaning of the results is interpreted and put into context (e.g., compared with other findings in the literature ), and its importance is assigned.
  • In the conclusion section, the results and the main conclusions are summarized.

A thesis is the most crucial document that you will write during your academic studies. For professional thesis editing and thesis proofreading services , visit Enago Thesis Editing for more information.

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Review Checklist

Have you  completed all data collection procedures and analyzed all results ?

Have you  included all results relevant to your thesis question, even if they do not support your hypothesis?

Have you reported the results  objectively , with no interpretation or speculation?

For quantitative research, have you included both  descriptive and  inferential statistical results and stated whether they support or contradict your hypothesis?

Have you used  tables and figures to present all results?

In your thesis body, have you presented only the pertinent results and elaborated on specific aspects that were presented in the tables and figures?

Are all tables and figures  correctly labeled and cited in numerical order in the text?

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We provide a report entailing recommendations for a single Plagiarism Check service. You can also write to us at [email protected] for further assistance as paraphrasing is sold offline and has a relatively high conversion in most geographies. 

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Please upload your research manuscript when you place the order. If you want to include the tables, charts, and figure legends in the plagiarism check, please ensure that all content is in editable formats and in one single document. 

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Acceptable repetition rate varies by journal but aim for low percentages (usually <5%). Avoid plagiarism, cite sources, and use detection tools. High plagiarism can lead to rejection, reputation damage, and serious consequences. Consult your institution for guidance on addressing plagiarism concerns.

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Home » Thesis – Structure, Example and Writing Guide

Thesis – Structure, Example and Writing Guide

Table of contents.

Thesis

Definition:

Thesis is a scholarly document that presents a student’s original research and findings on a particular topic or question. It is usually written as a requirement for a graduate degree program and is intended to demonstrate the student’s mastery of the subject matter and their ability to conduct independent research.

History of Thesis

The concept of a thesis can be traced back to ancient Greece, where it was used as a way for students to demonstrate their knowledge of a particular subject. However, the modern form of the thesis as a scholarly document used to earn a degree is a relatively recent development.

The origin of the modern thesis can be traced back to medieval universities in Europe. During this time, students were required to present a “disputation” in which they would defend a particular thesis in front of their peers and faculty members. These disputations served as a way to demonstrate the student’s mastery of the subject matter and were often the final requirement for earning a degree.

In the 17th century, the concept of the thesis was formalized further with the creation of the modern research university. Students were now required to complete a research project and present their findings in a written document, which would serve as the basis for their degree.

The modern thesis as we know it today has evolved over time, with different disciplines and institutions adopting their own standards and formats. However, the basic elements of a thesis – original research, a clear research question, a thorough review of the literature, and a well-argued conclusion – remain the same.

Structure of Thesis

The structure of a thesis may vary slightly depending on the specific requirements of the institution, department, or field of study, but generally, it follows a specific format.

Here’s a breakdown of the structure of a thesis:

This is the first page of the thesis that includes the title of the thesis, the name of the author, the name of the institution, the department, the date, and any other relevant information required by the institution.

This is a brief summary of the thesis that provides an overview of the research question, methodology, findings, and conclusions.

This page provides a list of all the chapters and sections in the thesis and their page numbers.

Introduction

This chapter provides an overview of the research question, the context of the research, and the purpose of the study. The introduction should also outline the methodology and the scope of the research.

Literature Review

This chapter provides a critical analysis of the relevant literature on the research topic. It should demonstrate the gap in the existing knowledge and justify the need for the research.

Methodology

This chapter provides a detailed description of the research methods used to gather and analyze data. It should explain the research design, the sampling method, data collection techniques, and data analysis procedures.

This chapter presents the findings of the research. It should include tables, graphs, and charts to illustrate the results.

This chapter interprets the results and relates them to the research question. It should explain the significance of the findings and their implications for the research topic.

This chapter summarizes the key findings and the main conclusions of the research. It should also provide recommendations for future research.

This section provides a list of all the sources cited in the thesis. The citation style may vary depending on the requirements of the institution or the field of study.

This section includes any additional material that supports the research, such as raw data, survey questionnaires, or other relevant documents.

How to write Thesis

Here are some steps to help you write a thesis:

  • Choose a Topic: The first step in writing a thesis is to choose a topic that interests you and is relevant to your field of study. You should also consider the scope of the topic and the availability of resources for research.
  • Develop a Research Question: Once you have chosen a topic, you need to develop a research question that you will answer in your thesis. The research question should be specific, clear, and feasible.
  • Conduct a Literature Review: Before you start your research, you need to conduct a literature review to identify the existing knowledge and gaps in the field. This will help you refine your research question and develop a research methodology.
  • Develop a Research Methodology: Once you have refined your research question, you need to develop a research methodology that includes the research design, data collection methods, and data analysis procedures.
  • Collect and Analyze Data: After developing your research methodology, you need to collect and analyze data. This may involve conducting surveys, interviews, experiments, or analyzing existing data.
  • Write the Thesis: Once you have analyzed the data, you need to write the thesis. The thesis should follow a specific structure that includes an introduction, literature review, methodology, results, discussion, conclusion, and references.
  • Edit and Proofread: After completing the thesis, you need to edit and proofread it carefully. You should also have someone else review it to ensure that it is clear, concise, and free of errors.
  • Submit the Thesis: Finally, you need to submit the thesis to your academic advisor or committee for review and evaluation.

Example of Thesis

Example of Thesis template for Students:

Title of Thesis

Table of Contents:

Chapter 1: Introduction

Chapter 2: Literature Review

Chapter 3: Research Methodology

Chapter 4: Results

Chapter 5: Discussion

Chapter 6: Conclusion

References:

Appendices:

Note: That’s just a basic template, but it should give you an idea of the structure and content that a typical thesis might include. Be sure to consult with your department or supervisor for any specific formatting requirements they may have. Good luck with your thesis!

Application of Thesis

Thesis is an important academic document that serves several purposes. Here are some of the applications of thesis:

  • Academic Requirement: A thesis is a requirement for many academic programs, especially at the graduate level. It is an essential component of the evaluation process and demonstrates the student’s ability to conduct original research and contribute to the knowledge in their field.
  • Career Advancement: A thesis can also help in career advancement. Employers often value candidates who have completed a thesis as it demonstrates their research skills, critical thinking abilities, and their dedication to their field of study.
  • Publication : A thesis can serve as a basis for future publications in academic journals, books, or conference proceedings. It provides the researcher with an opportunity to present their research to a wider audience and contribute to the body of knowledge in their field.
  • Personal Development: Writing a thesis is a challenging task that requires time, dedication, and perseverance. It provides the student with an opportunity to develop critical thinking, research, and writing skills that are essential for their personal and professional development.
  • Impact on Society: The findings of a thesis can have an impact on society by addressing important issues, providing insights into complex problems, and contributing to the development of policies and practices.

Purpose of Thesis

The purpose of a thesis is to present original research findings in a clear and organized manner. It is a formal document that demonstrates a student’s ability to conduct independent research and contribute to the knowledge in their field of study. The primary purposes of a thesis are:

  • To Contribute to Knowledge: The main purpose of a thesis is to contribute to the knowledge in a particular field of study. By conducting original research and presenting their findings, the student adds new insights and perspectives to the existing body of knowledge.
  • To Demonstrate Research Skills: A thesis is an opportunity for the student to demonstrate their research skills. This includes the ability to formulate a research question, design a research methodology, collect and analyze data, and draw conclusions based on their findings.
  • To Develop Critical Thinking: Writing a thesis requires critical thinking and analysis. The student must evaluate existing literature and identify gaps in the field, as well as develop and defend their own ideas.
  • To Provide Evidence of Competence : A thesis provides evidence of the student’s competence in their field of study. It demonstrates their ability to apply theoretical concepts to real-world problems, and their ability to communicate their ideas effectively.
  • To Facilitate Career Advancement : Completing a thesis can help the student advance their career by demonstrating their research skills and dedication to their field of study. It can also provide a basis for future publications, presentations, or research projects.

When to Write Thesis

The timing for writing a thesis depends on the specific requirements of the academic program or institution. In most cases, the opportunity to write a thesis is typically offered at the graduate level, but there may be exceptions.

Generally, students should plan to write their thesis during the final year of their graduate program. This allows sufficient time for conducting research, analyzing data, and writing the thesis. It is important to start planning the thesis early and to identify a research topic and research advisor as soon as possible.

In some cases, students may be able to write a thesis as part of an undergraduate program or as an independent research project outside of an academic program. In such cases, it is important to consult with faculty advisors or mentors to ensure that the research is appropriately designed and executed.

It is important to note that the process of writing a thesis can be time-consuming and requires a significant amount of effort and dedication. It is important to plan accordingly and to allocate sufficient time for conducting research, analyzing data, and writing the thesis.

Characteristics of Thesis

The characteristics of a thesis vary depending on the specific academic program or institution. However, some general characteristics of a thesis include:

  • Originality : A thesis should present original research findings or insights. It should demonstrate the student’s ability to conduct independent research and contribute to the knowledge in their field of study.
  • Clarity : A thesis should be clear and concise. It should present the research question, methodology, findings, and conclusions in a logical and organized manner. It should also be well-written, with proper grammar, spelling, and punctuation.
  • Research-Based: A thesis should be based on rigorous research, which involves collecting and analyzing data from various sources. The research should be well-designed, with appropriate research methods and techniques.
  • Evidence-Based : A thesis should be based on evidence, which means that all claims made in the thesis should be supported by data or literature. The evidence should be properly cited using appropriate citation styles.
  • Critical Thinking: A thesis should demonstrate the student’s ability to critically analyze and evaluate information. It should present the student’s own ideas and arguments, and engage with existing literature in the field.
  • Academic Style : A thesis should adhere to the conventions of academic writing. It should be well-structured, with clear headings and subheadings, and should use appropriate academic language.

Advantages of Thesis

There are several advantages to writing a thesis, including:

  • Development of Research Skills: Writing a thesis requires extensive research and analytical skills. It helps to develop the student’s research skills, including the ability to formulate research questions, design and execute research methodologies, collect and analyze data, and draw conclusions based on their findings.
  • Contribution to Knowledge: Writing a thesis provides an opportunity for the student to contribute to the knowledge in their field of study. By conducting original research, they can add new insights and perspectives to the existing body of knowledge.
  • Preparation for Future Research: Completing a thesis prepares the student for future research projects. It provides them with the necessary skills to design and execute research methodologies, analyze data, and draw conclusions based on their findings.
  • Career Advancement: Writing a thesis can help to advance the student’s career. It demonstrates their research skills and dedication to their field of study, and provides a basis for future publications, presentations, or research projects.
  • Personal Growth: Completing a thesis can be a challenging and rewarding experience. It requires dedication, hard work, and perseverance. It can help the student to develop self-confidence, independence, and a sense of accomplishment.

Limitations of Thesis

There are also some limitations to writing a thesis, including:

  • Time and Resources: Writing a thesis requires a significant amount of time and resources. It can be a time-consuming and expensive process, as it may involve conducting original research, analyzing data, and producing a lengthy document.
  • Narrow Focus: A thesis is typically focused on a specific research question or topic, which may limit the student’s exposure to other areas within their field of study.
  • Limited Audience: A thesis is usually only read by a small number of people, such as the student’s thesis advisor and committee members. This limits the potential impact of the research findings.
  • Lack of Real-World Application : Some thesis topics may be highly theoretical or academic in nature, which may limit their practical application in the real world.
  • Pressure and Stress : Writing a thesis can be a stressful and pressure-filled experience, as it may involve meeting strict deadlines, conducting original research, and producing a high-quality document.
  • Potential for Isolation: Writing a thesis can be a solitary experience, as the student may spend a significant amount of time working independently on their research and writing.

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ON YOUR 1ST ORDER

Mastering Dissertation Data Analysis: A Comprehensive Guide

By Laura Brown on 29th December 2023

To craft an effective dissertation data analysis chapter, you need to follow some simple steps:

  • Start by planning the structure and objectives of the chapter.
  • Clearly set the stage by providing a concise overview of your research design and methodology.
  • Proceed to thorough data preparation, ensuring accuracy and organisation.
  • Justify your methods and present the results using visual aids for clarity.
  • Discuss the findings within the context of your research questions.
  • Finally, review and edit your chapter to ensure coherence.

This approach will ensure a well-crafted and impactful analysis section.

Before delving into details on how you can come up with an engaging data analysis show in your dissertation, we first need to understand what it is and why it is required.

What Is Data Analysis In A Dissertation?

The data analysis chapter is a crucial section of a research dissertation that involves the examination, interpretation, and synthesis of collected data. In this chapter, researchers employ statistical techniques, qualitative methods, or a combination of both to make sense of the data gathered during the research process.

Why Is The Data Analysis Chapter So Important?

The primary objectives of the data analysis chapter are to identify patterns, trends, relationships, and insights within the data set. Researchers use various tools and software to conduct a thorough analysis, ensuring that the results are both accurate and relevant to the research questions or hypotheses. Ultimately, the findings derived from this chapter contribute to the overall conclusions of the dissertation, providing a basis for drawing meaningful and well-supported insights.

Steps Required To Craft Data Analysis Chapter To Perfection

Now that we have an idea of what a dissertation analysis chapter is and why it is necessary to put it in the dissertation, let’s move towards how we can create one that has a significant impact. Our guide will move around the bulleted points that have been discussed initially in the beginning. So, it’s time to begin.

Dissertation Data Analysis With 8 Simple Steps

Step 1: Planning Your Data Analysis Chapter

Planning your data analysis chapter is a critical precursor to its successful execution.

  • Begin by outlining the chapter structure to provide a roadmap for your analysis.
  • Start with an introduction that succinctly introduces the purpose and significance of the data analysis in the context of your research.
  • Following this, delineate the chapter into sections such as Data Preparation, where you detail the steps taken to organise and clean your data.
  • Plan on to clearly define the Data Analysis Techniques employed, justifying their relevance to your research objectives.
  • As you progress, plan for the Results Presentation, incorporating visual aids for clarity. Lastly, earmark a section for the Discussion of Findings, where you will interpret results within the broader context of your research questions.

This structured approach ensures a comprehensive and cohesive data analysis chapter, setting the stage for a compelling narrative that contributes significantly to your dissertation. You can always seek our dissertation data analysis help to plan your chapter.

Step 2: Setting The Stage – Introduction to Data Analysis

Your primary objective is to establish a solid foundation for the analytical journey. You need to skillfully link your data analysis to your research questions, elucidating the direct relevance and purpose of the upcoming analysis.

Simultaneously, define key concepts to provide clarity and ensure a shared understanding of the terms integral to your study. Following this, offer a concise overview of your data set characteristics, outlining its source, nature, and any noteworthy features.

This meticulous groundwork alongside our help with dissertation data analysis lays the base for a coherent and purposeful chapter, guiding readers seamlessly into the subsequent stages of your dissertation.

Step 3: Data Preparation

Now this is another pivotal phase in the data analysis process, ensuring the integrity and reliability of your findings. You should start with an insightful overview of the data cleaning and preprocessing procedures, highlighting the steps taken to refine and organise your dataset. Then, discuss any challenges encountered during the process and the strategies employed to address them.

Moving forward, delve into the specifics of data transformation procedures, elucidating any alterations made to the raw data for analysis. Clearly describe the methods employed for normalisation, scaling, or any other transformations deemed necessary. It will not only enhance the quality of your analysis but also foster transparency in your research methodology, reinforcing the robustness of your data-driven insights.

Step 4: Data Analysis Techniques

The data analysis section of a dissertation is akin to choosing the right tools for an artistic masterpiece. Carefully weigh the quantitative and qualitative approaches, ensuring a tailored fit for the nature of your data.

Quantitative Analysis

  • Descriptive Statistics: Paint a vivid picture of your data through measures like mean, median, and mode. It’s like capturing the essence of your data’s personality.
  • Inferential Statistics:Take a leap into the unknown, making educated guesses and inferences about your larger population based on a sample. It’s statistical magic in action.

Qualitative Analysis

  • Thematic Analysis: Imagine your data as a novel, and thematic analysis as the tool to uncover its hidden chapters. Dissect the narrative, revealing recurring themes and patterns.
  • Content Analysis: Scrutinise your data’s content like detectives, identifying key elements and meanings. It’s a deep dive into the substance of your qualitative data.

Providing Rationale for Chosen Methods

You should also articulate the why behind the chosen methods. It’s not just about numbers or themes; it’s about the story you want your data to tell. Through transparent rationale, you should ensure that your chosen techniques align seamlessly with your research goals, adding depth and credibility to the analysis.

Step 5: Presentation Of Your Results

You can simply break this process into two parts.

a.    Creating Clear and Concise Visualisations

Effectively communicate your findings through meticulously crafted visualisations. Use tables that offer a structured presentation, summarising key data points for quick comprehension. Graphs, on the other hand, visually depict trends and patterns, enhancing overall clarity. Thoughtfully design these visual aids to align with the nature of your data, ensuring they serve as impactful tools for conveying information.

b.    Interpreting and Explaining Results

Go beyond mere presentation by providing insightful interpretation by taking data analysis services for dissertation. Show the significance of your findings within the broader research context. Moreover, articulates the implications of observed patterns or relationships. By weaving a narrative around your results, you guide readers through the relevance and impact of your data analysis, enriching the overall understanding of your dissertation’s key contributions.

Step 6: Discussion of Findings

While discussing your findings and dissertation discussion chapter , it’s like putting together puzzle pieces to understand what your data is saying. You can always take dissertation data analysis help to explain what it all means, connecting back to why you started in the first place.

Be honest about any limitations or possible biases in your study; it’s like showing your cards to make your research more trustworthy. Comparing your results to what other smart people have found before you adds to the conversation, showing where your work fits in.

Looking ahead, you suggest ideas for what future researchers could explore, keeping the conversation going. So, it’s not just about what you found, but also about what comes next and how it all fits into the big picture of what we know.

Step 7: Writing Style and Tone

In order to perfectly come up with this chapter, follow the below points in your writing and adjust the tone accordingly,

  • Use clear and concise language to ensure your audience easily understands complex concepts.
  • Avoid unnecessary jargon in data analysis for thesis, and if specialised terms are necessary, provide brief explanations.
  • Keep your writing style formal and objective, maintaining an academic tone throughout.
  • Avoid overly casual language or slang, as the data analysis chapter is a serious academic document.
  • Clearly define terms and concepts, providing specific details about your data preparation and analysis procedures.
  • Use precise language to convey your ideas, minimising ambiguity.
  • Follow a consistent formatting style for headings, subheadings, and citations to enhance readability.
  • Ensure that tables, graphs, and visual aids are labelled and formatted uniformly for a polished presentation.
  • Connect your analysis to the broader context of your research by explaining the relevance of your chosen methods and the importance of your findings.
  • Offer a balance between detail and context, helping readers understand the significance of your data analysis within the larger study.
  • Present enough detail to support your findings but avoid overwhelming readers with excessive information.
  • Use a balance of text and visual aids to convey information efficiently.
  • Maintain reader engagement by incorporating transitions between sections and effectively linking concepts.
  • Use a mix of sentence structures to add variety and keep the writing engaging.
  • Eliminate grammatical errors, typos, and inconsistencies through thorough proofreading.
  • Consider seeking feedback from peers or mentors to ensure the clarity and coherence of your writing.

You can seek a data analysis dissertation example or sample from CrowdWriter to better understand how we write it while following the above-mentioned points.

Step 8: Reviewing and Editing

Reviewing and editing your data analysis chapter is crucial for ensuring its effectiveness and impact. By revising your work, you refine the clarity and coherence of your analysis, enhancing its overall quality.

Seeking feedback from peers, advisors or dissertation data analysis services provides valuable perspectives, helping identify blind spots and areas for improvement. Addressing common writing pitfalls, such as grammatical errors or unclear expressions, ensures your chapter is polished and professional.

Taking the time to review and edit not only strengthens the academic integrity of your work but also contributes to a final product that is clear, compelling, and ready for scholarly scrutiny.

Concluding On This Data Analysis Help

Be it master thesis data analysis, an undergraduate one or for PhD scholars, the steps remain almost the same as we have discussed in this guide. The primary focus is to be connected with your research questions and objectives while writing your data analysis chapter.

Do not lose your focus and choose the right analysis methods and design. Make sure to present your data through various visuals to better explain your data and engage the reader as well. At last, give it a detailed read and seek assistance from experts and your supervisor for further improvement.

Laura Brown

Laura Brown, a senior content writer who writes actionable blogs at Crowd Writer.

IMAGES

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COMMENTS

  1. Dissertation Results/Findings Chapter (Quantitative)

    The results chapter (also referred to as the findings or analysis chapter) is one of the most important chapters of your dissertation or thesis because it shows the reader what you've found in terms of the quantitative data you've collected. It presents the data using a clear text narrative, supported by tables, graphs and charts.

  2. PDF Chapter 4: Analysis and Interpretation of Results

    42. CHAPTER 4: ANALYSIS AND INTERPRETATION OF RESULTS. 4.1 INTRODUCTION. To complete this study properly, it is necessary to analyse the data collected in order to test the hypothesis and answer the research questions. As already indicated in the preceding chapter, data is interpreted in a descriptive form.

  3. Writing the Data Analysis Chapter(s): Results and Evidence

    Score 94% Score 94%. 4.4 Writing the Data Analysis Chapter (s): Results and Evidence. Unlike the introduction, literature review and methodology chapter (s), your results chapter (s) will need to be written for the first time as you draft your thesis even if you submitted a proposal, though this part of your thesis will certainly build upon the ...

  4. How to Write a Results Section

    The results chapter of a thesis or dissertation presents your research results concisely and objectively. In quantitative research, for each question or hypothesis, state: The type of analysis used; Relevant results in the form of descriptive and inferential statistics; Whether or not the alternative hypothesis was supported

  5. PDF A Complete Dissertation

    DISSERTATION CHAPTERS Order and format of dissertation chapters may vary by institution and department. 1. Introduction 2. Literature review 3. Methodology 4. Findings 5. Analysis and synthesis 6. Conclusions and recommendations Chapter 1: Introduction This chapter makes a case for the signifi-cance of the problem, contextualizes the

  6. Dissertations 5: Findings, Analysis and Discussion: Home

    if you write a scientific dissertation, or anyway using quantitative methods, you will have some objective results that you will present in the Results chapter. You will then interpret the results in the Discussion chapter. B) More common for qualitative methods. - Analysis chapter. This can have more descriptive/thematic subheadings.

  7. How Do I Write the Methods Chapter?

    The different sections the methods chapter typically has including design, sample, measures, ethics and data analysis paragraphs, will be outlined, and there are also some general tips for writing your methods chapter in a scientific manner. ... This chapter should help you write the methods chapter of your dissertation in a step-by-step ...

  8. How Do I Write the Discussion Chapter?

    The Discussion chapter brings an opportunity to write an academic argument that contains a detailed critical evaluation and analysis of your research findings. This chapter addresses the purpose and critical nature of the discussion, contains a guide to selecting key results to discuss, and details how best to structure the discussion with ...

  9. Dissertation & Thesis Outline

    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. Tip You can find a thesis and dissertation outline template below, as well as a chapter outline example, ...

  10. Chapter Summary & Overview

    Chapter Summary in Thesis. In a Thesis, the Chapter Summary is a section that provides a brief overview of the main points covered in each chapter of the thesis. It is usually included at the beginning or end of each chapter and is intended to help the reader understand the key concepts and ideas presented in the chapter.

  11. How to Write a Dissertation Discussion Chapter

    The dissertation analysis & discussion chapter is usually very long, so it will make sense to emphasise the critical points in a concluding paragraph so the reader can grasp the essential information. This will also help to make sure the reader understands your analysis. Also Read: Research Discussion Of Findings. Useful Tips

  12. How to write the analysis and discussion chapters in qualitative (SSAH

    The discussion chapters form the heart of your thesis and this is where your unique contribution comes to the forefront. This is where your data takes centre-stage and where you get to showcase your original arguments, perspectives and knowledge. To do this effectively needs you to explore the original themes and issues arising from and within ...

  13. Thesis

    How to Write a Discussion (Analysis) Chapter in a Thesis. Discussion and analysis are probably the most critical components of any thesis. These are also the longest sections of your thesis, which require thoroughness, conciseness, attention to detail, brevity, and extensive use of primary and secondary evidence.

  14. Dissertation Results/Findings Chapter (Quantitative)

    What exactly is the results chapter? The results chapter (also referred to as the findings or analysis chapter) shall one of the most important chapters of your dissertation or thesis because it exhibitions the reader what you've found in terms of the quantitative data you've collected.It presents the date using ampere clear write narrative, supported the charts, diagram and charts.

  15. Thesis chapter

    A thesis is built up of a series of chapters that construct a substantiated and convincing response to the research question (s). Typically, a thesis contains the following chapters: an introduction; a literature review; a description of methodology; a report and discussion of results; and a conclusion. A thesis may have five to eight chapters ...

  16. How to Write an Impressive Thesis Results Section

    What should the thesis results section include? Include all relevant results as text, tables, or figures. Report the results of subject recruitment and data collection. For qualitative research, present the data from all statistical analyses, whether or not the results are significant. For quantitative research, present the data by coding or ...

  17. How to Do Thematic Analysis

    How to Do Thematic Analysis | Step-by-Step Guide & Examples. Published on September 6, 2019 by Jack Caulfield.Revised on June 22, 2023. Thematic analysis is a method of analyzing qualitative data.It is usually applied to a set of texts, such as an interview or transcripts.The researcher closely examines the data to identify common themes - topics, ideas and patterns of meaning that come up ...

  18. Thesis

    This chapter provides a critical analysis of the relevant literature on the research topic. It should demonstrate the gap in the existing knowledge and justify the need for the research. ... [The abstract is a brief summary of your thesis, usually around 150-250 words, that provides an overview of your research question, methodology, findings ...

  19. Introduction and conclusion thesis chapters

    This chapter is your opportunity to leave a strong impression on the reader (assessors) about the strength and relevance of your research, and your skills as a researcher. Importantly, the conclusion chapter must link with your introduction chapter to complete the framing of the thesis and demonstrate that you have achieved what you set out to do.

  20. Dissertation Data Analysis: A Quick Help With 8 Steps

    The data analysis chapter is a crucial section of a research dissertation that involves the examination, interpretation, and synthesis of collected data. In this chapter, researchers employ statistical techniques, qualitative methods, or a combination of both to make sense of the data gathered during the research process.