how to present questionnaire results in dissertation

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Harvard University Program on Survey Research

• How to Frame and Explain the Survey Data Used in a Thesis

Surveys are a special research tool with strengths, weaknesses, and a language all of their own. There are many different steps to designing and conducting a survey, and survey researchers have specific ways of describing what they do.

This handout, based on an annual workshop offered by the Program on Survey Research at Harvard, is geared toward undergraduate honors thesis writers using survey data.

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How to Write an Impressive Thesis Results Section

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.

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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How To Write The Results/Findings Chapter

For qualitative studies (dissertations & theses).

By: Jenna Crossley (PhD). Expert Reviewed By: Dr. Eunice Rautenbach | August 2021

So, you’ve collected and analysed your qualitative data, and it’s time to write up your results chapter. But where do you start? In this post, we’ll guide you through the qualitative results chapter (also called the findings chapter), step by step. 

Overview: Qualitative Results Chapter

• What (exactly) the qualitative results chapter is
• What to include in your results chapter
• How to write up your results chapter
• A few tips and tricks to help you along the way
• Free results chapter template

What exactly is the results chapter?

The results chapter in a dissertation or thesis (or any formal academic research piece) is where you objectively and neutrally present the findings of your qualitative analysis (or analyses if you used multiple qualitative analysis methods ). This chapter can sometimes be combined with the discussion chapter (where you interpret the data and discuss its meaning), depending on your university’s preference.  We’ll treat the two chapters as separate, as that’s the most common approach.

In contrast to a quantitative results chapter that presents numbers and statistics, a qualitative results chapter presents data primarily in the form of words . But this doesn’t mean that a qualitative study can’t have quantitative elements – you could, for example, present the number of times a theme or topic pops up in your data, depending on the analysis method(s) you adopt.

Adding a quantitative element to your study can add some rigour, which strengthens your results by providing more evidence for your claims. This is particularly common when using qualitative content analysis. Keep in mind though that qualitative research aims to achieve depth, richness and identify nuances , so don’t get tunnel vision by focusing on the numbers. They’re just cream on top in a qualitative analysis.

So, to recap, the results chapter is where you objectively present the findings of your analysis, without interpreting them (you’ll save that for the discussion chapter). With that out the way, let’s take a look at what you should include in your results chapter.

What should you include in the results chapter?

As we’ve mentioned, your qualitative results chapter should purely present and describe your results , not interpret them in relation to the existing literature or your research questions . Any speculations or discussion about the implications of your findings should be reserved for your discussion chapter.

In your results chapter, you’ll want to talk about your analysis findings and whether or not they support your hypotheses (if you have any). Naturally, the exact contents of your results chapter will depend on which qualitative analysis method (or methods) you use. For example, if you were to use thematic analysis, you’d detail the themes identified in your analysis, using extracts from the transcripts or text to support your claims.

While you do need to present your analysis findings in some detail, you should avoid dumping large amounts of raw data in this chapter. Instead, focus on presenting the key findings and using a handful of select quotes or text extracts to support each finding . The reams of data and analysis can be relegated to your appendices.

While it’s tempting to include every last detail you found in your qualitative analysis, it is important to make sure that you report only that which is relevant to your research aims, objectives and research questions .  Always keep these three components, as well as your hypotheses (if you have any) front of mind when writing the chapter and use them as a filter to decide what’s relevant and what’s not.

Need a helping hand?

How do I write the results chapter?

Now that we’ve covered the basics, it’s time to look at how to structure your chapter. Broadly speaking, the results chapter needs to contain three core components – the introduction, the body and the concluding summary. Let’s take a look at each of these.

Section 1: Introduction

The first step is to craft a brief introduction to the chapter. This intro is vital as it provides some context for your findings. In your introduction, you should begin by reiterating your problem statement and research questions and highlight the purpose of your research . Make sure that you spell this out for the reader so that the rest of your chapter is well contextualised.

The next step is to briefly outline the structure of your results chapter. In other words, explain what’s included in the chapter and what the reader can expect. In the results chapter, you want to tell a story that is coherent, flows logically, and is easy to follow , so make sure that you plan your structure out well and convey that structure (at a high level), so that your reader is well oriented.

The introduction section shouldn’t be lengthy. Two or three short paragraphs should be more than adequate. It is merely an introduction and overview, not a summary of the chapter.

Pro Tip – To help you structure your chapter, it can be useful to set up an initial draft with (sub)section headings so that you’re able to easily (re)arrange parts of your chapter. This will also help your reader to follow your results and give your chapter some coherence.  Be sure to use level-based heading styles (e.g. Heading 1, 2, 3 styles) to help the reader differentiate between levels visually. You can find these options in Word (example below).

Section 2: Body

Before we get started on what to include in the body of your chapter, it’s vital to remember that a results section should be completely objective and descriptive, not interpretive . So, be careful not to use words such as, “suggests” or “implies”, as these usually accompany some form of interpretation – that’s reserved for your discussion chapter.

The structure of your body section is very important , so make sure that you plan it out well. When planning out your qualitative results chapter, create sections and subsections so that you can maintain the flow of the story you’re trying to tell. Be sure to systematically and consistently describe each portion of results. Try to adopt a standardised structure for each portion so that you achieve a high level of consistency throughout the chapter.

For qualitative studies, results chapters tend to be structured according to themes , which makes it easier for readers to follow. However, keep in mind that not all results chapters have to be structured in this manner. For example, if you’re conducting a longitudinal study, you may want to structure your chapter chronologically. Similarly, you might structure this chapter based on your theoretical framework . The exact structure of your chapter will depend on the nature of your study , especially your research questions.

As you work through the body of your chapter, make sure that you use quotes to substantiate every one of your claims . You can present these quotes in italics to differentiate them from your own words. A general rule of thumb is to use at least two pieces of evidence per claim, and these should be linked directly to your data. Also, remember that you need to include all relevant results , not just the ones that support your assumptions or initial leanings.

In addition to including quotes, you can also link your claims to the data by using appendices , which you should reference throughout your text. When you reference, make sure that you include both the name/number of the appendix , as well as the line(s) from which you drew your data.

As referencing styles can vary greatly, be sure to look up the appendix referencing conventions of your university’s prescribed style (e.g. APA , Harvard, etc) and keep this consistent throughout your chapter.

Section 3: Concluding summary

The concluding summary is very important because it summarises your key findings and lays the foundation for the discussion chapter . Keep in mind that some readers may skip directly to this section (from the introduction section), so make sure that it can be read and understood well in isolation.

In this section, you need to remind the reader of the key findings. That is, the results that directly relate to your research questions and that you will build upon in your discussion chapter. Remember, your reader has digested a lot of information in this chapter, so you need to use this section to remind them of the most important takeaways.

Importantly, the concluding summary should not present any new information and should only describe what you’ve already presented in your chapter. Keep it concise – you’re not summarising the whole chapter, just the essentials.

Tips for writing an A-grade results chapter

Now that you’ve got a clear picture of what the qualitative results chapter is all about, here are some quick tips and reminders to help you craft a high-quality chapter:

• Your results chapter should be written in the past tense . You’ve done the work already, so you want to tell the reader what you found , not what you are currently finding .
• Make sure that you review your work multiple times and check that every claim is adequately backed up by evidence . Aim for at least two examples per claim, and make use of an appendix to reference these.
• When writing up your results, make sure that you stick to only what is relevant . Don’t waste time on data that are not relevant to your research objectives and research questions.
• Use headings and subheadings to create an intuitive, easy to follow piece of writing. Make use of Microsoft Word’s “heading styles” and be sure to use them consistently.
• When referring to numerical data, tables and figures can provide a useful visual aid. When using these, make sure that they can be read and understood independent of your body text (i.e. that they can stand-alone). To this end, use clear, concise labels for each of your tables or figures and make use of colours to code indicate differences or hierarchy.
• Similarly, when you’re writing up your chapter, it can be useful to highlight topics and themes in different colours . This can help you to differentiate between your data if you get a bit overwhelmed and will also help you to ensure that your results flow logically and coherently.

If you have any questions, leave a comment below and we’ll do our best to help. If you’d like 1-on-1 help with your results chapter (or any chapter of your dissertation or thesis), check out our private dissertation coaching service here or book a free initial consultation to discuss how we can help you.

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20 Comments

This was extremely helpful. Thanks a lot guys

Hi, thanks for the great research support platform created by the gradcoach team!

I wanted to ask- While “suggests” or “implies” are interpretive terms, what terms could we use for the results chapter? Could you share some examples of descriptive terms?

I think that instead of saying, ‘The data suggested, or The data implied,’ you can say, ‘The Data showed or revealed, or illustrated or outlined’…If interview data, you may say Jane Doe illuminated or elaborated, or Jane Doe described… or Jane Doe expressed or stated.

I found this article very useful. Thank you very much for the outstanding work you are doing.

What if i have 3 different interviewees answering the same interview questions? Should i then present the results in form of the table with the division on the 3 perspectives or rather give a results in form of the text and highlight who said what?

I think this tabular representation of results is a great idea. I am doing it too along with the text. Thanks

That was helpful was struggling to separate the discussion from the findings

this was very useful, Thank you.

Very helpful, I am confident to write my results chapter now.

It is so helpful! It is a good job. Thank you very much!

Very useful, well explained. Many thanks.

Hello, I appreciate the way you provided a supportive comments about qualitative results presenting tips

I loved this! It explains everything needed, and it has helped me better organize my thoughts. What words should I not use while writing my results section, other than subjective ones.

Thanks a lot, it is really helpful

Thank you so much dear, i really appropriate your nice explanations about this.

Thank you so much for this! I was wondering if anyone could help with how to prproperly integrate quotations (Excerpts) from interviews in the finding chapter in a qualitative research. Please GradCoach, address this issue and provide examples.

what if I’m not doing any interviews myself and all the information is coming from case studies that have already done the research.

Very helpful thank you.

This was very helpful as I was wondering how to structure this part of my dissertation, to include the quotes… Thanks for this explanation

This is very helpful, thanks! I am required to write up my results chapters with the discussion in each of them – any tips and tricks for this strategy?

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Dissertation Results Section Writing Guide

Introduction.

Once you have carried out your research, you will be presented with a set of either quantitative or qualitative data. In your methodology you will have already stated which analytical technique you are planning to use to organise and present the findings from the research.

A good results section (or chapter) will answer the research questions with the use of the findings from the research. An easier way to organise the results section would be to present the research question and to then answer it with the results from the experiment.

In order to interpret the findings, you will need to use either a qualitative or quantitative analytical technique.

Qualitative Techniques

The most common qualitative research techniques are observations, questionnaires, interviews and focus groups. If you used any of these in your research, then you will need to analyse the data using either content analysis, narrative analysis, thematic analysis, framework analysis, discourse analysis and grounded theory.

Qualitative analysis involves coding the data sets to organise the results. Due to the results not being quantifiable, it is often difficult to determine the output of the results. Once the findings have been coded and a key has been produced, any trends or commonalities can be determined.

Quantitative Techniques

As the data collected will be in numerical form, in order to understand and interpret the outcome of those figures, it is necessary to choose an analytical technique that will allow the data set to be analysed to produce a specific outcome that will address the research question posed or to determine the relationship between one independent variable and an outcome variable.

Writing The Results Section

To make the dissertation easier to interpret, it is best to have a results chapter and then a discussion chapter separately. By separating these two sections, you are then able to present the findings and then interpret them and review them against any secondary data found in the literature review or in the conceptual framework.

Always make sure that you speak to your supervisor or check your university’s guidelines before structuring your dissertation. Some universities will have a specific structure that they would like you to follow (e.g. separating the results and the discussion chapters) .

Depending on what type of data you have, you may need to create graphics, diagrams and tables. It is encouraged that these are to be used as it can be easier for not only you, but also the reader to understand any themes, trends or abnormalities in the results.

Although it is encouraged to use tables, diagrams and graphics in the work, it is also a necessity that you ensure that you explain the meaning of the data in text. This allows for further detail and interpretation to be given.

At times, it is also good to compare the results with any secondary research that would validate your findings. For example, in your literature review, if you found that a study of a similar nature yielded the same results or findings, when presenting your results, it can be good to refer to this as validation of your findings.

Due to word count restrictions of dissertations, presenting every single piece of data collected could take up a significant portion of the word count. For this reason, it is good to present a full set of the data collected in the appendices  and refer to this in the text (e.g. Appendix 1, Appendix 2 etc.).

A brief example of something that would be found in an appendix would be a transcript from any interviews carried out. If presenting numerical data and statistical analysis, any data that perhaps does not directly answer a research question but is relevant in the overall findings of the work would be placed in an appendix and referred to in the work.

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If you require assistance to write the results section of your dissertation, you may want to consider our helpful service which is a great way to get a head start on your work.

Checklist: Writing Dissertation Results

• Have I presented my data in a clear and easy-to-understand way?
• Have I used graphs/charts/tables wherever this is relevant?
• Have I made sure the data is presented in a logical order?
• Have I added necessary appendices and referred to them in the text?

Congratulations!

Well done on completing this checklist! You're doing great.

Dissertation Results FAQ's

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Our dissertation writing guide chapters .

• Dissertation Writing Guide
• Dissertation Topic
• Dissertation Title
• Dissertation Proposal
• Dissertation Abstract
• Dissertation Introduction
• Dissertation Background
• Literature Review
• Dissertation Methodology
• Dissertation Results Section
• Dissertation Discussion
• Dissertation Conclusion

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How to Write the Results Section of your Dissertation or Thesis?

Introduction

Organizing your results, providing context, presenting the data in results section, describing statistical analysis, reporting the findings in results section, supporting the findings, visual representation in results section.

As you progress on your journey towards completing your PhD or Post Graduate dissertation, one of the most critical sections that holds immense significance is the results section.

Results section serves as the pinnacle of your research, where you unveil the outcomes of your exhaustive efforts and shed light on the answers to your research questions. In this blog post, we will delve into the intricacies of the results section and explore how to effectively present and interpret your findings to leave a lasting impact.

Whether you’re conducting research in the field of biology, psychology, computer science, or any other discipline, the results section is where your data takes center stage. It is a space where you showcase your meticulous analysis, statistical methods, and the discoveries you’ve made along the way. By understanding the key components and best practices for constructing a compelling results section, you can present your findings in a manner that resonates with both your academic peers and the wider research community.

In this comprehensive guide, we will walk you through the fundamental elements of the results section, from organizing your data to choosing the appropriate visual representations. We will explore the importance of clear and concise reporting, emphasizing the significance of providing contextual information and highlighting any unexpected or groundbreaking discoveries.

Furthermore, we will discuss strategies for effectively interpreting your results, discussing their implications, and connecting them back to your research objectives. By mastering these skills, you will be able to demonstrate the significance of your work, contribute to the existing body of knowledge, and potentially pave the way for further research in your field.

Throughout the blog post, I will provide concrete examples from various disciplines to illustrate the implementation of these techniques. Additionally, I will offer valuable tips on avoiding common pitfalls, ensuring the accuracy and reliability of your results, and seeking feedback from your advisors or peers to enhance the quality of your analysis.

If you are in paucity of time, not confident of your writing skills and in a hurry to complete the writing task then you can think of hiring a research consultant that solves all your problems. Please visit my article on Hiring a Research consultant for your PhD tasks for further details.

Organizing the results of your study in a logical and coherent manner is crucial for effectively communicating your findings. By presenting your results in an organized structure, you enhance the clarity and readability of your dissertation. Here are some key considerations for organizing your results:

• Research studies often involve complex algorithms, software implementations, experimental data, and performance metrics. It is essential to organize these diverse elements in a cohesive manner to make it easier for readers to follow your research. A well-structured results section enables readers to understand the progression of your experiments and the relationship between different findings.
• Begin by reminding readers of the research questions or hypotheses that guided your study. This alignment helps establish a clear connection between the objectives of your research and the subsequent presentation of results. For example, if your research question focuses on evaluating the efficiency of a new sorting algorithm, you would present the experimental data, performance metrics, and comparative analyses specific to that algorithm in relation to the research question.
• Subsubsection 1.1: Experimental Setup
• Subsubsection 1.2: Experimental Results and Analysis
• Subsubsection 2.1: Performance Metrics
• Subsubsection 2.2: Comparative Results and Discussion

Remember to tailor the organization of your results section to the specific requirements of your research. The key is to provide a logical flow and structure that enables readers to easily comprehend and interpret your findings.

Providing context for the results of your study is essential to help readers understand the significance and implications of your findings. By offering background information and study design details, you establish a foundation upon which the results can be properly interpreted. Here are some key considerations for providing context:

• Before delving into the results, it is important to provide readers with relevant background information about the topic or problem being addressed. This may include a literature review of existing research, theories, or methodologies in the field. By doing so, you situate your work within the broader landscape of and demonstrate its relevance. Additionally, explain the design of your study, such as the specific algorithms, software frameworks, datasets, or hardware setups used. This ensures that readers understand the context in which your results were obtained.
• Provide a brief overview of the current state-of-the-art in image recognition algorithms and their limitations.
• Explain the specific challenges or gaps in the existing methods that motivated your research.
• Describe the design of your study, including the choice of machine learning techniques, datasets used for training and evaluation, preprocessing steps, and any hardware or software configurations.

By providing context, you allow readers to understand the background, motivation, and methodology behind your research. This sets the stage for better comprehension and interpretation of your results. Contextualizing your findings, as it helps establish the relevance, novelty, and potential impact of your research within the larger field.

Presenting data in a clear and organized manner is crucial for effectively communicating your results. The way you present your data can greatly impact the reader’s understanding and interpretation of your findings. Here are some key considerations for presenting data:

• Presenting performance metrics of different algorithms using a table to allow for easy comparison.
• Using a line graph to depict the improvement in accuracy over training iterations in a machine learning model.
• Employing a bar chart to compare the execution times of different algorithms on a specific dataset.
• Clear labelling and formatting of your data ensure that readers can easily understand and interpret the information presented. Label each table, figure, chart, or graph with a concise and descriptive title. Ensure that axes, legends, and labels are clearly labelled and units of measurement are specified. Use appropriate fonts, colours, and styles to enhance readability. Consider providing captions or footnotes to provide additional context or explanations where necessary.
• In the text, refer to a specific table presenting the accuracy results of different algorithms and explain how these results support your research hypothesis or contribute to the field.
• Discuss a figure showing the relationship between the number of training examples and the performance of a machine learning model, emphasizing its implications for scalability and generalization.

By presenting data in a visually appealing and well-organized manner, you enhance the clarity and accessibility of your results. Proper labelling, formatting, and referring to each table or figure in the text help readers navigate the information and grasp its significance. Remember to choose the most appropriate format for your data and use visuals to support and reinforce your findings.

The inclusion of statistical analyses in the results section is crucial for providing objective and quantitative evidence to support your findings. Statistical analyses help you draw meaningful conclusions from your data and determine the significance of observed results. Here are some key considerations for describing statistical analyses:

• Statistical analyses play a vital role in determining the reliability and significance of your findings. They provide a systematic and objective framework for interpreting the data and testing hypotheses. Discuss the importance of including statistical analyses in the results section to demonstrate the rigour and validity of your research.
• Describe using a t-test to compare the means of two groups in a user study, as it is appropriate for assessing the statistical significance of differences.
• Explain employing logistic regression to model the relationship between independent variables and a binary outcome in a predictive analytics study.
• Report the p-value as 0.032, indicating a statistically significant difference between the two groups at the 0.05 significance level.
• Interpret an effect size of 0.40 as a medium-sized effect, highlighting its practical importance in the context of the research.

By describing the statistical analyses conducted, explaining the rationale behind the chosen tests, and accurately presenting the statistical values and interpretations, you strengthen the validity and reliability of your findings. Statistical analyses provide an objective framework for drawing conclusions from your data and lend credibility to your research in the computer science domain.

Reporting the findings of your research in an objective, concise, and clear manner is essential for effectively communicating your results. Here are some key considerations for reporting the findings:

• Summarize the key findings of a machine learning study by stating that “the proposed algorithm achieved an average accuracy of 85% on the test dataset, outperforming existing state-of-the-art methods by 10%.”
• For a research question about the impact of different programming languages on software performance, present specific metrics such as execution time or memory usage for each language, along with a comparison and interpretation of the results.
• Instead of using overly technical language, communicate the results in a more accessible way: “The experimental results showed a significant correlation between the number of training samples and the accuracy of the model, indicating that a larger training dataset leads to improved prediction performance.”

By guiding readers on summarizing the results objectively and concisely, addressing each research question or hypothesis, and using clear and concise language, you ensure that your findings are communicated effectively. This approach allows readers to understand the core contributions of your research and how they align with the research questions or hypotheses you set out to investigate.

Providing strong evidence from the data to support your findings, addressing unexpected or contradictory results, and discussing limitations and potential explanations are essential components of reporting research findings. Here are some key considerations for supporting the findings:

• Present empirical evidence from a user study, such as participant feedback or performance metrics, to support the usability and effectiveness of a proposed user interface design.
• If a software system performed unexpectedly poorly in certain scenarios, discuss potential factors such as data bias, implementation issues, or limitations of the evaluation methodology that could have influenced the results.
• Acknowledge limitations such as a small sample size, limited dataset availability, or computational constraints that might affect the generalizability or robustness of the results.
• Discuss potential explanations for unexpected results, such as issues with data quality, algorithmic complexity, or model assumptions.

By providing evidence from the data to support the findings, addressing unexpected or contradictory results, and discussing limitations and potential explanations, you demonstrate a rigorous and reflective approach to your research in the computer science domain. This allows readers to assess the strength and reliability of your findings and gain a deeper understanding of the nuances and implications of your work.

Using visual representations, such as tables, graphs, and figures, alongside the text can greatly enhance the understanding and impact of your findings. Here are some key considerations for visual representation:

Visual representations offer several benefits in presenting research findings. They provide a concise and intuitive way to convey complex information, trends, and patterns. Visuals can help readers grasp key insights at a glance, enhance the overall readability of the document, and make the findings more memorable. Visual representations also facilitate effective comparisons, highlight important relationships, and aid in storytelling. Example:

When creating visual representations, consider the following tips to ensure clarity and effectiveness: a. Choose the appropriate visual format: Select the most suitable format, such as tables, line graphs, scatter plots, or heatmaps, based on the nature of the data and the message you want to convey.

b. Simplify and declutter: Avoid overwhelming the visuals with excessive data points, labels, or unnecessary decorations. Keep the design clean and focused on conveying the essential information.

c. Label and title clearly: Provide descriptive and informative titles for tables, graphs, and figures. Label the axes, data points, or components clearly to facilitate understanding.

d. Use colors and visual cues purposefully: Utilize colors and visual cues to highlight important information or differentiate between categories. Ensure that the chosen colors are distinguishable and accessible. e. Provide legends and captions: Include legends to explain symbols, colors, or abbreviations used in the visuals. Provide informative captions or annotations to guide readers in interpreting the visuals accurately. Example:

By incorporating clear and effective visual representations alongside the text, you enhance the presentation and understanding of your research findings in the computer science domain. Well-designed tables, graphs, and figures can simplify complex information, facilitate comparisons, and enhance the visual appeal of your dissertation. Remember to choose appropriate formats, keep the visuals uncluttered, label clearly, and use colors and visual cues purposefully to maximize their impact.

Writing the results section of a dissertation or thesis is a critical task that requires careful attention to detail, organization, and effective communication. Throughout this blog post, we have explored key elements to consider when crafting this section.

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Reporting Research Results in APA Style | Tips & Examples

Published on December 21, 2020 by Pritha Bhandari . Revised on January 17, 2024.

The results section of a quantitative research paper is where you summarize your data and report the findings of any relevant statistical analyses.

The APA manual provides rigorous guidelines for what to report in quantitative research papers in the fields of psychology, education, and other social sciences.

Use these standards to answer your research questions and report your data analyses in a complete and transparent way.

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Table of contents

What goes in your results section, introduce your data, summarize your data, report statistical results, presenting numbers effectively, what doesn’t belong in your results section, frequently asked questions about results in apa.

In APA style, the results section includes preliminary information about the participants and data, descriptive and inferential statistics, and the results of any exploratory analyses.

Include these in your results section:

• Participant flow and recruitment period. Report the number of participants at every stage of the study, as well as the dates when recruitment took place.
• Missing data . Identify the proportion of data that wasn’t included in your final analysis and state the reasons.
• Any adverse events. Make sure to report any unexpected events or side effects (for clinical studies).
• Descriptive statistics . Summarize the primary and secondary outcomes of the study.
• Inferential statistics , including confidence intervals and effect sizes. Address the primary and secondary research questions by reporting the detailed results of your main analyses.
• Results of subgroup or exploratory analyses, if applicable. Place detailed results in supplementary materials.

Write up the results in the past tense because you’re describing the outcomes of a completed research study.

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Before diving into your research findings, first describe the flow of participants at every stage of your study and whether any data were excluded from the final analysis.

Participant flow and recruitment period

It’s necessary to report any attrition, which is the decline in participants at every sequential stage of a study. That’s because an uneven number of participants across groups sometimes threatens internal validity and makes it difficult to compare groups. Be sure to also state all reasons for attrition.

If your study has multiple stages (e.g., pre-test, intervention, and post-test) and groups (e.g., experimental and control groups), a flow chart is the best way to report the number of participants in each group per stage and reasons for attrition.

Also report the dates for when you recruited participants or performed follow-up sessions.

Missing data

Another key issue is the completeness of your dataset. It’s necessary to report both the amount and reasons for data that was missing or excluded.

Data can become unusable due to equipment malfunctions, improper storage, unexpected events, participant ineligibility, and so on. For each case, state the reason why the data were unusable.

Some data points may be removed from the final analysis because they are outliers—but you must be able to justify how you decided what to exclude.

If you applied any techniques for overcoming or compensating for lost data, report those as well.

Adverse events

For clinical studies, report all events with serious consequences or any side effects that occured.

Descriptive statistics summarize your data for the reader. Present descriptive statistics for each primary, secondary, and subgroup analysis.

Don’t provide formulas or citations for commonly used statistics (e.g., standard deviation) – but do provide them for new or rare equations.

Descriptive statistics

The exact descriptive statistics that you report depends on the types of data in your study. Categorical variables can be reported using proportions, while quantitative data can be reported using means and standard deviations . For a large set of numbers, a table is the most effective presentation format.

Include sample sizes (overall and for each group) as well as appropriate measures of central tendency and variability for the outcomes in your results section. For every point estimate , add a clearly labelled measure of variability as well.

Be sure to note how you combined data to come up with variables of interest. For every variable of interest, explain how you operationalized it.

According to APA journal standards, it’s necessary to report all relevant hypothesis tests performed, estimates of effect sizes, and confidence intervals.

When reporting statistical results, you should first address primary research questions before moving onto secondary research questions and any exploratory or subgroup analyses.

Present the results of tests in the order that you performed them—report the outcomes of main tests before post-hoc tests, for example. Don’t leave out any relevant results, even if they don’t support your hypothesis.

Inferential statistics

For each statistical test performed, first restate the hypothesis , then state whether your hypothesis was supported and provide the outcomes that led you to that conclusion.

Report the following for each hypothesis test:

• the test statistic value,
• the degrees of freedom ,
• the exact p- value (unless it is less than 0.001),
• the magnitude and direction of the effect.

When reporting complex data analyses, such as factor analysis or multivariate analysis, present the models estimated in detail, and state the statistical software used. Make sure to report any violations of statistical assumptions or problems with estimation.

Effect sizes and confidence intervals

For each hypothesis test performed, you should present confidence intervals and estimates of effect sizes .

Confidence intervals are useful for showing the variability around point estimates. They should be included whenever you report population parameter estimates.

Effect sizes indicate how impactful the outcomes of a study are. But since they are estimates, it’s recommended that you also provide confidence intervals of effect sizes.

Subgroup or exploratory analyses

Briefly report the results of any other planned or exploratory analyses you performed. These may include subgroup analyses as well.

Subgroup analyses come with a high chance of false positive results, because performing a large number of comparison or correlation tests increases the chances of finding significant results.

If you find significant results in these analyses, make sure to appropriately report them as exploratory (rather than confirmatory) results to avoid overstating their importance.

While these analyses can be reported in less detail in the main text, you can provide the full analyses in supplementary materials.

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To effectively present numbers, use a mix of text, tables , and figures where appropriate:

• To present three or fewer numbers, try a sentence ,
• To present between 4 and 20 numbers, try a table ,
• To present more than 20 numbers, try a figure .

Since these are general guidelines, use your own judgment and feedback from others for effective presentation of numbers.

Tables and figures should be numbered and have titles, along with relevant notes. Make sure to present data only once throughout the paper and refer to any tables and figures in the text.

Formatting statistics and numbers

It’s important to follow capitalization , italicization, and abbreviation rules when referring to statistics in your paper. There are specific format guidelines for reporting statistics in APA , as well as general rules about writing numbers .

If you are unsure of how to present specific symbols, look up the detailed APA guidelines or other papers in your field.

It’s important to provide a complete picture of your data analyses and outcomes in a concise way. For that reason, raw data and any interpretations of your results are not included in the results section.

It’s rarely appropriate to include raw data in your results section. Instead, you should always save the raw data securely and make them available and accessible to any other researchers who request them.

Making scientific research available to others is a key part of academic integrity and open science.

Interpretation or discussion of results

This belongs in your discussion section. Your results section is where you objectively report all relevant findings and leave them open for interpretation by readers.

While you should state whether the findings of statistical tests lend support to your hypotheses, refrain from forming conclusions to your research questions in the results section.

Explanation of how statistics tests work

For the sake of concise writing, you can safely assume that readers of your paper have professional knowledge of how statistical inferences work.

In an APA results section , you should generally report the following:

• Participant flow and recruitment period.
• Missing data and any adverse events.
• Descriptive statistics about your samples.
• Inferential statistics , including confidence intervals and effect sizes.
• Results of any subgroup or exploratory analyses, if applicable.

According to the APA guidelines, you should report enough detail on inferential statistics so that your readers understand your analyses.

• the test statistic value
• the degrees of freedom
• the exact p value (unless it is less than 0.001)
• the magnitude and direction of the effect

You should also present confidence intervals and estimates of effect sizes where relevant.

In APA style, statistics can be presented in the main text or as tables or figures . To decide how to present numbers, you can follow APA guidelines:

• To present three or fewer numbers, try a sentence,
• To present between 4 and 20 numbers, try a table,
• To present more than 20 numbers, try a figure.

Results are usually written in the past tense , because they are describing the outcome of completed actions.

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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How to Write a Results Section for a Dissertation or Research Paper: Guide & Examples

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A results section is a crucial part of a research paper or dissertation, where you analyze your major findings. This section goes beyond simply presenting study outcomes. You should also include a comprehensive statistical analysis and interpret the collected data in detail.

Without dissertation research results, it is impossible to imagine a scientific work. Your task here is to present your study findings. What are qualitative or quantitative indicators? How to use tables and diagrams? How to describe data? Our article answers all these questions and many more. So, read further to discover how to analyze and describe your research indexes or contact or professionals for dissertation help from StudyCrumb.

What Is a Results Section of Dissertation?

The results section of a dissertation is a data statement from your research. Here you should present the main findings of your study to your readers. This section aims to show information objectively, systematically, concisely. It is allowed using text supplemented with illustrations.  In general, this section's length is not limited but should include all necessary data. Interpretations or conclusions should not be included in this section. Therefore, in theory, this is one of your shortest sections. But it can also be one of the most challenging sections.  The introduction presents a research topic and answers the question "why?". The Methods section explains the data collection process and answers "how?". Meanwhile, the result section shows actual data gained from experiments and tells "what?" Thus, this part plays a critical role in highlighting study's relevance. This chapter gives reader study relevance with novelty. So, you should figure out how to write it correctly. Here are main tasks that you should keep in mind while writing:

• Results answer the question "What was found in your research?"
• Results contain only your study's outcome. They do not include comments or interpretations.
• Results must always be presented accurately & objectively.
• Tables & figures are used to draw readers' attention. But the same data should never be presented in the form of a table and a figure. Don't repeat anything from a table also in text.

Dissertation: Results vs Discussion vs Conclusion

Results and discussion sections of a dissertation are often confused among researchers. Sometimes both these parts are mixed up with a conclusion for thesis . Figured out what is covered in each of these important chapters. Your readers should see that you notice how different they are. A clear understanding of differences will help you write your dissertation more effectively. 5 differences between Results VS Discussion VS Conclusion:

Wanna figure out the actual difference between discussion vs conclusion? Check out our helpful articles about Dissertation Discussion or Dissertation Conclusion.

Present Your Findings When Writing Results Section of Dissertation

Now it's time to understand how to arrange the results section of the dissertation. First, present most general findings, then narrow it down to a more specific one. Describe both qualitative & quantitative results. For example, imagine you are comparing the behavior of hamsters and mice. First, say a few words about the behavioral type of mammals that you studied. Then, mention rodents in general. At end, describe specific species of animals you carried out an experiment on.

Qualitative Results Section in Dissertation

In your dissertation results section, qualitative data may not be directly related to specific sub-questions or hypotheses. You can structure this chapter around main issues that arise when analyzing data. For each question, make a general observation of what data show. For example, you may recall recurring agreements or differences, patterns, trends. Personal answers are the basis of your research. Clarify and support these views with direct quotes. Add more information to the thesis appendix if it's needed.

Quantitative Results Section in a Dissertation

The easiest way to write a quantitative dissertation results section is to build it around a sub-question or hypothesis of your research. For each subquery, provide relevant results and include statistical analysis . Then briefly evaluate importance & reliability. Notice how each result relates to the problem or whether it supports the hypothesis. Focus on key trends, differences, and relationships between data. But don't speculate about their meaning or consequences. This should be put in the discussion vs conclusion section. Suppose your results are not directly related to answering your questions. Maybe there is additional information that helps readers understand how you collect data. In that case, you can include them in the appendix. It is often helpful to include visual elements such as graphs, charts, and tables. But only if they accurately support your results and add value.

Tables and Figures in Results Section in Dissertation

We recommend you use tables or figures in the dissertation results section correctly. Such interpretation can effectively present complex data concisely and visually. It allows readers to quickly gain a statistical overview. On the contrary, poorly designed graphs can confuse readers. That will reduce the effectiveness of your article.  Here are our recommendations that help you understand how to use tables and figures:

• Make sure tables and figures are self-explanatory. Sometimes, your readers may look at tables and figures before reading the entire text. So they should make sense as separate elements.
• Do not repeat the content of tables and figures in text. Text can be used to highlight key points from tables and figures. But do not repeat every element.
• Make sure that values ​​or information in tables and text are consistent. Make sure that abbreviations, group names, interpretations are the same as in text.
• Use clear, informative titles for tables and figures. Do not leave any table or figure without a title or legend. Otherwise, readers will not be able to understand data's meaning. Also, make sure column names, labels, figures are understandable.
• Check accuracy of data presented in tables and figures. Always double-check tables and figures to make sure numbers converge.
• Tables should not contain redundant information. Make sure tables in the article are not too crowded. If you need to provide extensive data, use Appendixes.
• Make sure images are clear. Make sure images and all parts of drawings are precise. Lettering should be in a standard font and legible against the background of the picture.
• Ask for permission to use illustrations. If you use illustrations, be sure to ask copyright holders and indicate them.

Tips on How to Write a Results Section

We have prepared several tips on how to write the results section of the dissertation!  Present data collected during study objectively, logically, and concisely. Highlight most important results and organize them into specific sections. It is an excellent way to show that you have covered all the descriptive information you need. Correct usage of visual elements effectively helps your readers with understanding. So, follow main 3 rules for writing this part:

• State only actual results. Leave explanations and comments for Discussion.
• Use text, tables, and pictures to orderly highlight key results.
• Make sure that contents of tables and figures are not repeated in text.

In case you have questions about a  conceptual framework in research , you will find a blog dedicated to this issue in our database.

What to Avoid When Writing the Results Section of a Dissertation

Here we will discuss how NOT to write the results section of a dissertation. Or simply, what points to avoid:

• Do not make your research too complicated. Your paper, tables, and graphs should be clearly marked and follow order. So that they can exist independently without further explanation.
• Do not include raw data. Remember, you are summarizing relevant results, not reporting them in detail. This chapter should briefly summarize your findings. Avoid complete introduction to each number and calculation.
• Do not contradict errors or false results. Explain these errors and contradictions in conclusions. This often happens when different research methods have been used.
• Do not write a conclusion or discussion. Instead, this part should contain summaries of findings.
• Do not tend to include explanations and inferences from results. Such an approach can make this chapter subjective, unclear, and confusing to the reader.
• Do not forget about novelty. Its lack is one of the main reasons for the paper's rejection.

Dissertation Results Section Example

Let's take a look at some good results section of dissertation examples. Remember that this part shows fundamental research you've done in detail. So, it has to be clear and concise, as you can see in the sample.

Final Thoughts on Writing Results Section of Dissertation

When writing a results section of a dissertation, highlight your achievements by data. The main chapter's task is to convince the reader of conclusions' validity of your research. You should not overload text with too detailed information. Never use words whose meanings you do not understand. Also, oversimplification may seem unconvincing for readers. But on the other hand, writing this part can even be fun. You can directly see your study results, which you'll interpret later. So keep going, and we wish you courage!

Writing any academic paper is long and thorough work. But StudyCrumb got you back! Our professional writers will deliver any type of work quickly and excellently! 

Joe Eckel is an expert on Dissertations writing. He makes sure that each student gets precious insights on composing A-grade academic writing.

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How to Write the Dissertation Findings or Results – Steps & Tips

Published by Grace Graffin at August 11th, 2021 , Revised On June 11, 2024

Each  part of the dissertation is unique, and some general and specific rules must be followed. The dissertation’s findings section presents the key results of your research without interpreting their meaning .

Theoretically, this is an exciting section of a dissertation because it involves writing what you have observed and found. However, it can be a little tricky if there is too much information to confuse the readers.

The goal is to include only the essential and relevant findings in this section. The results must be presented in an orderly sequence to provide clarity to the readers.

This section of the dissertation should be easy for the readers to follow, so you should avoid going into a lengthy debate over the interpretation of the results.

It is vitally important to focus only on clear and precise observations. The findings chapter of the  dissertation  is theoretically the easiest to write.

It includes  statistical analysis and a brief write-up about whether or not the results emerging from the analysis are significant. This segment should be written in the past sentence as you describe what you have done in the past.

This article will provide detailed information about  how to   write the findings of a dissertation .

When to Write Dissertation Findings Chapter

As soon as you have gathered and analysed your data, you can start to write up the findings chapter of your dissertation paper. Remember that it is your chance to report the most notable findings of your research work and relate them to the research hypothesis  or  research questions set out in  the introduction chapter of the dissertation .

You will be required to separately report your study’s findings before moving on to the discussion chapter  if your dissertation is based on the  collection of primary data  or experimental work.

However, you may not be required to have an independent findings chapter if your dissertation is purely descriptive and focuses on the analysis of case studies or interpretation of texts.

• Always report the findings of your research in the past tense.
• The dissertation findings chapter varies from one project to another, depending on the data collected and analyzed.
• Avoid reporting results that are not relevant to your research questions or research hypothesis.

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1. Reporting Quantitative Findings

The best way to present your quantitative findings is to structure them around the research  hypothesis or  questions you intend to address as part of your dissertation project.

Report the relevant findings for each research question or hypothesis, focusing on how you analyzed them.

Analysis of your findings will help you determine how they relate to the different research questions and whether they support the hypothesis you formulated.

While you must highlight meaningful relationships, variances, and tendencies, it is important not to guess their interpretations and implications because this is something to save for the discussion  and  conclusion  chapters.

Any findings not directly relevant to your research questions or explanations concerning the data collection process  should be added to the dissertation paper’s appendix section.

Use of Figures and Tables in Dissertation Findings

Suppose your dissertation is based on quantitative research. In that case, it is important to include charts, graphs, tables, and other visual elements to help your readers understand the emerging trends and relationships in your findings.

Repeating information will give the impression that you are short on ideas. Refer to all charts, illustrations, and tables in your writing but avoid recurrence.

The text should be used only to elaborate and summarize certain parts of your results. On the other hand, illustrations and tables are used to present multifaceted data.

It is recommended to give descriptive labels and captions to all illustrations used so the readers can figure out what each refers to.

How to Report Quantitative Findings

Here is an example of how to report quantitative results in your dissertation findings chapter;

Two hundred seventeen participants completed both the pretest and post-test and a Pairwise T-test was used for the analysis. The quantitative data analysis reveals a statistically significant difference between the mean scores of the pretest and posttest scales from the Teachers Discovering Computers course. The pretest mean was 29.00 with a standard deviation of 7.65, while the posttest mean was 26.50 with a standard deviation of 9.74 (Table 1). These results yield a significance level of .000, indicating a strong treatment effect (see Table 3). With the correlation between the scores being .448, the little relationship is seen between the pretest and posttest scores (Table 2). This leads the researcher to conclude that the impact of the course on the educators’ perception and integration of technology into the curriculum is dramatic.

Paired Samples

Paired Samples Correlation

Paired Samples Test

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

2. Reporting Qualitative Findings

A notable issue with reporting qualitative findings is that not all results directly relate to your research questions or hypothesis.

The best way to present the results of qualitative research is to frame your findings around the most critical areas or themes you obtained after you examined the data.

In-depth data analysis will help you observe what the data shows for each theme. Any developments, relationships, patterns, and independent responses directly relevant to your research question or hypothesis should be mentioned to the readers.

Additional information not directly relevant to your research can be included in the appendix .

How to Report Qualitative Findings

Here is an example of how to report qualitative results in your dissertation findings chapter;

The last question of the interview focused on the need for improvement in Thai ready-to-eat products and the industry at large, emphasizing the need for enhancement in the current products being offered in the market. When asked if there was any particular need for Thai ready-to-eat meals to be improved and how to improve them in case of ‘yes,’ the males replied mainly by saying that the current products need improvement in terms of the use of healthier raw materials and preservatives or additives. There was an agreement amongst all males concerning the need to improve the industry for ready-to-eat meals and the use of more healthy items to prepare such meals. The females were also of the opinion that the fast-food items needed to be improved in the sense that more healthy raw materials such as vegetable oil and unsaturated fats, including whole-wheat products, to overcome risks associated with trans fat leading to obesity and hypertension should be used for the production of RTE products. The frozen RTE meals and packaged snacks included many preservatives and chemical-based flavouring enhancers that harmed human health and needed to be reduced. The industry is said to be aware of this fact and should try to produce RTE products that benefit the community in terms of healthy consumption.

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What to Avoid in Dissertation Findings Chapter

• Avoid using interpretive and subjective phrases and terms such as “confirms,” “reveals,” “suggests,” or “validates.” These terms are more suitable for the discussion chapter , where you will be expected to interpret the results in detail.
• Only briefly explain findings in relation to the key themes, hypothesis, and research questions. You don’t want to write a detailed subjective explanation for any research questions at this stage.

The Do’s of Writing the Findings or Results Section

• Ensure you are not presenting results from other research studies in your findings.
• Observe whether or not your hypothesis is tested or research questions answered.
• Illustrations and tables present data and are labelled to help your readers understand what they relate to.
• Use software such as Excel, STATA, and SPSS to analyse results and important trends.

Essential Guidelines on How to Write Dissertation Findings

The dissertation findings chapter should provide the context for understanding the results. The research problem should be repeated, and the research goals should be stated briefly.

This approach helps to gain the reader’s attention toward the research problem. The first step towards writing the findings is identifying which results will be presented in this section.

The results relevant to the questions must be presented, considering whether the results support the hypothesis. You do not need to include every result in the findings section. The next step is ensuring the data can be appropriately organized and accurate.

You will need to have a basic idea about writing the findings of a dissertation because this will provide you with the knowledge to arrange the data chronologically.

Start each paragraph by writing about the most important results and concluding the section with the most negligible actual results.

A short paragraph can conclude the findings section, summarising the findings so readers will remember as they transition to the next chapter. This is essential if findings are unexpected or unfamiliar or impact the study.

Our writers can help you with all parts of your dissertation, including statistical analysis of your results . To obtain free non-binding quotes, please complete our online quote form here .

Be Impartial in your Writing

When crafting your findings, knowing how you will organize the work is important. The findings are the story that needs to be told in response to the research questions that have been answered.

Therefore, the story needs to be organized to make sense to you and the reader. The findings must be compelling and responsive to be linked to the research questions being answered.

Always ensure that the size and direction of any changes, including percentage change, can be mentioned in the section. The details of p values or confidence intervals and limits should be included.

The findings sections only have the relevant parts of the primary evidence mentioned. Still, it is a good practice to include all the primary evidence in an appendix that can be referred to later.

The results should always be written neutrally without speculation or implication. The statement of the results mustn’t have any form of evaluation or interpretation.

Negative results should be added in the findings section because they validate the results and provide high neutrality levels.

The length of the dissertation findings chapter is an important question that must be addressed. It should be noted that the length of the section is directly related to the total word count of your dissertation paper.

The writer should use their discretion in deciding the length of the findings section or refer to the dissertation handbook or structure guidelines.

It should neither belong nor be short nor concise and comprehensive to highlight the reader’s main findings.

Ethically, you should be confident in the findings and provide counter-evidence. Anything that does not have sufficient evidence should be discarded. The findings should respond to the problem presented and provide a solution to those questions.

Structure of the Findings Chapter

The chapter should use appropriate words and phrases to present the results to the readers. Logical sentences should be used, while paragraphs should be linked to produce cohesive work.

You must ensure all the significant results have been added in the section. Recheck after completing the section to ensure no mistakes have been made.

The structure of the findings section is something you may have to be sure of primarily because it will provide the basis for your research work and ensure that the discussions section can be written clearly and proficiently.

One way to arrange the results is to provide a brief synopsis and then explain the essential findings. However, there should be no speculation or explanation of the results, as this will be done in the discussion section.

Another way to arrange the section is to present and explain a result. This can be done for all the results while the section is concluded with an overall synopsis.

This is the preferred method when you are writing more extended dissertations. It can be helpful when multiple results are equally significant. A brief conclusion should be written to link all the results and transition to the discussion section.

Numerous data analysis dissertation examples are available on the Internet, which will help you improve your understanding of writing the dissertation’s findings.

Problems to Avoid When Writing Dissertation Findings

One of the problems to avoid while writing the dissertation findings is reporting background information or explaining the findings. This should be done in the introduction section .

You can always revise the introduction chapter based on the data you have collected if that seems an appropriate thing to do.

Raw data or intermediate calculations should not be added in the findings section. Always ask your professor if raw data needs to be included.

If the data is to be included, then use an appendix or a set of appendices referred to in the text of the findings chapter.

Do not use vague or non-specific phrases in the findings section. It is important to be factual and concise for the reader’s benefit.

The findings section presents the crucial data collected during the research process. It should be presented concisely and clearly to the reader. There should be no interpretation, speculation, or analysis of the data.

The significant results should be categorized systematically with the text used with charts, figures, and tables. Furthermore, avoiding using vague and non-specific words in this section is essential.

It is essential to label the tables and visual material properly. You should also check and proofread the section to avoid mistakes.

The dissertation findings chapter is a critical part of your overall dissertation paper. If you struggle with presenting your results and statistical analysis, our expert dissertation writers can help you get things right. Whether you need help with the entire dissertation paper or individual chapters, our dissertation experts can provide customized dissertation support .

FAQs About Findings of a Dissertation

How do i report quantitative findings.

The best way to present your quantitative findings is to structure them around the research hypothesis or research questions you intended to address as part of your dissertation project. Report the relevant findings for each of the research questions or hypotheses, focusing on how you analyzed them.

How do I report qualitative findings?

The best way to present the qualitative research results is to frame your findings around the most important areas or themes that you obtained after examining the data.

An in-depth analysis of the data will help you observe what the data is showing for each theme. Any developments, relationships, patterns, and independent responses that are directly relevant to your research question or hypothesis should be clearly mentioned for the readers.

Can I use interpretive phrases like ‘it confirms’ in the finding chapter?

No, It is highly advisable to avoid using interpretive and subjective phrases in the finding chapter. These terms are more suitable for the discussion chapter , where you will be expected to provide your interpretation of the results in detail.

Can I report the results from other research papers in my findings chapter?

NO, you must not be presenting results from other research studies in your findings.

You May Also Like

If your dissertation includes many abbreviations, it would make sense to define all these abbreviations in a list of abbreviations in alphabetical order.

When writing your dissertation, an abstract serves as a deal maker or breaker. It can either motivate your readers to continue reading or discourage them.

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

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Think Postgrad

Find out how to use a dissertation questionnaire for your masters.

Prof Martyn Denscombe, author of " The Good Research Guide, 6th edition ", gives expert advice on using a questionnaire survey for your postgraduate dissertation.

Questionnaire surveys are a well-established way of collecting data. They work with relatively small-scale research projects so design and deliver research questionnaires quickly and cheaply. When it comes to conducting research for a master’s dissertation, questionnaire surveys feature prominently as the method of choice.

Using the post for bulky and lengthy surveys is normal. Sometimes questionnaires go by hand. The popularity of questionnaire surveys is principally due to the benefits of using online web-based questionnaires. There are two main aspects to this.

Designing questionnaires

First, the software for producing and delivering web questionnaires. Simple to use features such as drop-down menus and tick-box answers, is user-friendly and inexpensive.

Second, online surveys make it possible to contact people across the globe without travelling anywhere. Given the time and resource constraints faced when producing a dissertation, makes online surveys all the more enticing. Social media such as Facebook, Instagram and WhatsApp is great for contacting people to participate in the survey.

In the context of a master’s dissertation, however, the quality of the survey data is a vital issue. The grade for the dissertation will depend on being able to defend the use of the data from the survey. This is the basis for advanced, master’s level academic enquiry.

Pro's and con's

It is not good enough to simply rely on getting 100 or so people to complete your questionnaire. Be aware of the pros and cons of questionnaire surveys. You need to justify the value of the data you have collected in the face of probing questions, such as:

• Who are the respondents and how they were selected?
• How representative are the respondents of the whole group being studied?
• What response rate was achieved by the survey?
• Are the questions suitable in relation to the topic and the particular respondents?
• What likelihood is there that respondents gave honest answers to the questions?

This is where The Good Research Guide, 6th edition becomes so valuable.

It identifies the key points that need to be addressed in order to conduct a competent questionnaire survey. It gets right to the heart of the matter, with plenty of practical guidance on how to deal with issues.

In a straightforward style, using plain language, this bestselling book covers a range of alternative strategies and methods for conducting small-scale social research projects and outlines some of the main ways in which the data can be analysed.

Read Prof Martyn Denscombe's advice on using a Case Study for your postgraduate dissertation.

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How to Present Dissertation Findings

The presentation of dissertation findings is a critical component in the successful completion of a master’s degree program. As the culmination of years of hard work, research, and dedication, your dissertation stands as a testament to your academic prowess and your ability to contribute meaningfully to your chosen field. Effectively presenting your findings not only demonstrates your mastery of the subject matter but also allows you to communicate your research’s significance to a broader audience. A well-crafted presentation of findings can facilitate a greater understanding and appreciation of your research, paving the way for future opportunities in academia or professional settings.

This article aims to provide a comprehensive guide for master’s degree candidates seeking to present their dissertation findings effectively. We will cover how to present dissertation findings, the essential aspects such as interpreting your findings, structuring your findings section, articulating results with clarity and precision, employing visual aids, contextualizing findings within the scholarly discourse, and preparing an engaging oral presentation. By following the guidelines and recommendations outlined in this article, you will be well-equipped to deliver a compelling, informative, and polished presentation of your dissertation findings.

Comprehending and Interpreting Your Findings

To effectively present your dissertation findings, you must first have a thorough understanding of the results obtained through your research. This begins with the application of suitable data analysis techniques, which may involve quantitative methods such as descriptive statistics, inferential statistics, and regression analysis, or qualitative approaches like thematic analysis, content analysis, or grounded theory. Selecting the appropriate method depends on your research questions, objectives, and the nature of the data collected. By employing suitable techniques, you can derive meaningful insights from your data and facilitate a more accurate interpretation of your findings.

Key Themes and Patterns

Once you have analyzed your data, it is crucial to identify the most significant themes and patterns that emerge from the results. This process requires a critical and analytical mindset, as well as a deep understanding of your research objectives and the theoretical underpinnings of your study. By focusing on the most salient findings, you can effectively communicate the essence of your research to your audience. Additionally, this will allow you to prioritize information and prevent information overload, making your presentation more accessible and engaging.

Ensuring Methodological Rigor and Credibility

To establish confidence in your findings, you must demonstrate that your research methods and data analysis techniques are rigorous and credible. This involves adhering to established methodological standards and practices within your field, as well as addressing potential threats to the validity and reliability of your results. For qualitative research, this may include addressing issues related to credibility, transferability, dependability, and confirmability. For quantitative research, it is essential to consider aspects like internal and external validity, reliability, and generalizability. By ensuring methodological rigor, you enhance the credibility of your findings and foster trust in your research among your audience.

Constructing a Coherent Findings Section

An effective findings section is organized in a manner that clearly demonstrates the relationship between your results and your research questions or objectives. To achieve this, present your findings by addressing each research question or objective systematically, thereby providing a coherent and logical structure to your presentation. This approach not only enhances the readability and comprehensibility of your findings section but also allows your audience to quickly grasp the significance of your results in the context of your study’s overarching goals.

As you present each finding, it is essential to contextualize it within the broader research landscape, discussing how it relates to existing knowledge and scholarship in your field. This may involve comparing and contrasting your results with those of previous studies, highlighting any similarities or discrepancies, and explaining possible reasons for the observed patterns. By providing this context, you enable your audience to better appreciate the novelty, relevance, and implications of your findings.

Establish a Logical Progression

To enhance the readability and organization of your findings section, make use of headings and subheadings to delineate different aspects of your results. These textual markers can help guide your audience through the structure of your findings, enabling them to follow your argument more easily. Ensure that your headings and subheadings accurately reflect the content of each section and are formatted consistently throughout the document.

Striking a Balance Between Textual Exposition and Visual Representation

A well-crafted findings section strikes a balance between textual exposition and visual representation, ensuring that your results are presented in a manner that is both accessible and engaging. Textual descriptions should be clear, concise, and focused, providing sufficient detail without overwhelming the reader. Visual representations, such as tables, charts, and graphs, should be employed judiciously to complement and clarify your textual exposition, presenting complex data in a more easily digestible format. Carefully consider the most effective way to present each finding, and strive to create a harmonious interplay between text and visuals that enhances the overall impact and comprehensibility of your findings section.

Articulating Findings with Clarity and Precision

To ensure that your findings are accessible to a wide range of audiences, including those outside your immediate field of expertise, employ clear and lucid language throughout your presentation. This involves avoiding excessive jargon, convoluted sentence structures, and overly complex vocabulary. By using straightforward and comprehensible language, you increase the likelihood that your research will be understood and appreciated by a diverse audience, thereby amplifying its impact and relevance.

When discussing complex concepts, theories, or methodologies, strive to elucidate them using accessible terminology and simple explanations. This may involve breaking down complicated ideas into their constituent parts or providing analogies, examples, or illustrations to facilitate understanding. Ensuring that your audience grasps these intricate concepts is vital for them to fully appreciate the significance of your findings and their implications for your field.

Accentuating Salient Points While Avoiding Redundancy

To maintain the interest and engagement of your audience, focus on accentuating the most salient points of your findings while avoiding unnecessary repetition or extraneous details. This involves carefully selecting the information to be presented and highlighting its relevance to your research questions or objectives. By distilling your findings down to their essential elements, you provide your audience with a concise and coherent overview of your results, enabling them to more readily grasp the key takeaways from your research.

When presenting your findings, it is crucial to exercise meticulousness and accuracy in reporting your results. This involves ensuring that all data, statistics, and calculations are correct and that any claims made are substantiated by the evidence provided. Additionally, be transparent about any limitations or uncertainties associated with your findings, acknowledging potential sources of error or bias. By adhering to these standards, you enhance the credibility of your research and foster trust in your findings among your audience.

Employing Visual Aids to Reinforce Findings

Visual aids, such as tables, charts, and graphs, can significantly enhance the presentation of your dissertation findings by providing a succinct and visually appealing representation of complex data. When selecting visual aids, consider which format best conveys the information you wish to highlight and which is most appropriate for your research context. Ensure that the chosen visual aids align with your research objectives and contribute meaningfully to the overall narrative of your findings.

To maximize the effectiveness of your visual aids, ensure that they are both comprehensible and aesthetically appealing. This involves using clear, legible fonts and labels, employing appropriate color schemes, and maintaining a consistent visual style throughout your presentation. Additionally, consider the use of white space and other design elements to enhance the readability and visual appeal of your visual aids. By attending to these details, you create visual aids that effectively support your findings and engage your audience.

Consistent Labeling and Formatting Practices

Consistency is crucial when employing visual aids in your dissertation findings. This includes using consistent labeling conventions, such as capitalization, abbreviation, and numbering, as well as maintaining a uniform style in terms of fonts, colors, and formatting. By adhering to these practices, you create a cohesive and polished presentation that enhances the professionalism and credibility of your research.

Seamlessly Incorporating Visual Aids Within the Narrative

Finally, to ensure that your visual aids effectively support your findings, it is essential to seamlessly incorporate them within the narrative of your presentation. This involves referencing each visual aid in the accompanying text, explaining its relevance, and discussing any key insights or patterns it reveals. By integrating your visual aids into the narrative in this manner, you create a cohesive and engaging presentation that effectively conveys the significance of your findings to your audience.

Contextualizing Findings within the Scholarly Discourse

To contextualize your findings within the broader scholarly discourse, draw connections between your results and existing research in your field. This may involve discussing how your findings align with, challenge, or expand upon previous studies, highlighting any similarities or discrepancies, and providing possible explanations for these observations. By drawing these connections, you demonstrate your awareness of the current state of knowledge and establish your research’s relevance within the wider academic landscape.

Emphasize the novelty and relevance of your investigation by highlighting how your research contributes to the existing body of knowledge. This may involve underscoring the unique aspects of your study, such as the research questions, methodology, or context, and discussing how these elements distinguish your research from previous investigations. By showcasing the novelty and relevance of your work, you demonstrate its value and significance within your discipline.

Identifying Lacunae Your Research Addresses in the Literature

Another way to contextualize your findings within the scholarly discourse is by identifying gaps or lacunae in the existing literature that your research addresses. By pinpointing these gaps and discussing how your findings help fill them, you underscore the importance of your research and its potential to advance the understanding of your field.

Deliberating on the Implications and Limitations of Your Findings

To discuss the implications of your findings, relate them to the relevant theories and conceptual frameworks that underpin your study. This may involve examining how your results support, challenge, or extend these theoretical frameworks and discussing the potential ramifications of your findings for the development of new theories or the refinement of existing ones.

It is crucial to acknowledge and evaluate the limitations and boundaries of your findings. This may involve discussing any methodological limitations, the generalizability of your results, or the potential biases inherent in your study. By addressing these issues, you demonstrate your awareness of the complexities and nuances of your research, fostering trust and credibility among your audience.

Based on the implications and limitations of your findings, propose potential avenues for future research. This may involve suggesting new research questions, methodologies, or contexts for investigation that could help advance the understanding of your field. By identifying these future research directions, you demonstrate the ongoing relevance and importance of your work within the academic community.

Elucidating the Ramifications of Your Findings for the Discipline

Finally, consider the broader ramifications of your findings for your discipline. This may involve discussing how your results contribute to the development of new knowledge, inform practice or policy, or inspire further inquiry in your field. By elucidating these ramifications, you underscore the significance of your research and its potential to make a lasting impact on your discipline.

Preparing an Engaging Oral Presentation of Findings

To support your oral presentation of findings , create a visually appealing and informative slideshow. Ensure that your slides are well-designed, employing a clear and readable font, appropriate colors, and relevant visuals, such as charts, graphs, or images. Limit the amount of text on each slide, focusing on key points and findings, and use bullet points or concise phrases to convey information effectively.

Develop your public speaking skills by practicing techniques such as maintaining eye contact, speaking clearly and confidently, using effective body language, and varying your tone and pace to maintain audience interest. Engage your audience by incorporating storytelling elements, sharing anecdotes, or posing thought-provoking questions throughout your presentation.

Anticipating and Addressing Potential inquiries and Critiques

Prepare for potential questions or critiques by anticipating the inquiries your audience may have and addressing them proactively in your presentation. Familiarize yourself with common concerns or objections within your field and be ready to respond to them with evidence-based arguments and counterpoints.

Organize your presentation in a logical and coherent manner, starting with an introduction that sets the stage for your findings, followed by a clear and succinct presentation of your results, and concluding with a summary of the main points and implications of your research. Avoid tangents or unnecessary digressions, and maintain a steady pace throughout your presentation.

Fostering Audience Participation

Encourage audience participation by incorporating interactive elements into your presentation, such as live polls, group discussions, or question-and-answer sessions. By fostering audience engagement, you create a dynamic and stimulating environment that enhances the overall impact and effectiveness of your presentation .

Soliciting Feedback and Refining Your Presentation

Solicit feedback on your presentation from peers, mentors, or advisors to gain valuable insights and suggestions for improvement. Encourage them to provide honest and constructive criticism, and be open to their perspectives and ideas.

Revise your presentation based on the feedback you receive, focusing on areas where improvements can be made or where further clarification is needed. This may involve refining your slide design, adjusting the organization of your presentation, or enhancing your public speaking skills.

Rehearse to Hone Your Delivery Skills

Practice your presentation multiple times, either alone or in front of a supportive audience, to build confidence and fine-tune your delivery. Use these rehearsal sessions to work on pacing, tone, and body language, as well as to familiarize yourself with your content and anticipate potential questions or critiques.

In Conclusion

Effectively presenting dissertation findings is crucial for demonstrating the significance and implications of your research within the academic community. By comprehending and interpreting your findings, constructing a coherent findings section, articulating results with clarity and precision, employing visual aids, contextualizing findings within the scholarly discourse, deliberating on implications and limitations, preparing an engaging oral presentation, and refining your presentation through feedback and rehearsal, you can master the art of presenting your dissertation findings.

Embracing these strategies and principles will enable you to communicate your research in a compelling, informative, and engaging manner, contributing to the advancement of your field and bolstering your academic and professional prospects.

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The main purpose of a dissertation is to contribute knowledge to your field of study. So it goes without saying that a dissertation is rather pointless if you don’t document the results of your research clearly! This is where you document the findings of your research, where you make sense of what you have discovered throughout the research process and explain its relevance to the research question or problem. Let’s explore how to write the results section of your dissertation.

What goes in the results section

Conventionally, the results section is the fourth chapter of your dissertation, written after you present your method of study . How exactly you present your findings differs from study to study, depending on the topic and discipline your research is situated in, the methods you used, and what kind of data you are presenting. 

Here’s what you’ll cover in the results chapter: 

• A brief reminder of the research question and the purpose of your research  
• The results of your experiment or study and what they mean 
• The data that you’ve collected in sentence form, accompanied by visual elements such as tables, graphs, charts, etc. 
• A critical analysis of how they relate to your research question 

Pro-tip: Always check your university’s guidelines for specific details on what you are required to write about in this section.

Results vs discussion

It’s important to note that the results chapter is usually not the same as the discussion . The purpose of the results section is to present findings in a logical, objective, and impartial manner. At this stage, you do not include your interpretation as a researcher or discuss the implications of the research. Observations that you make, as a researcher, are better suited for the next few chapters. In other words, you simply present the data in the results chapter, and you interpret it in the discussion chapter. 

Although, in some cases (for instance, if your university tells you to), you may be asked to combine the two sections. In this case, you’ll have to weave your interpretation and analysis into the segments where you’re presenting data. 

How to write and structure the results section

Regardless of whether your dissertation is qualitative or quantitative in nature, there are certain aspects common to this chapter. It has an introduction that reiterates the aims and purpose of the research, a body that deconstructs the results obtained during the research process, and a conclusion that summarizes the study’s findings and sets the stage for a discussion about its implications for your research area. 

This chapter is written in the simple past tense, as you are reporting a study that has been conducted in the past. 

Reporting qualitative research 

The purpose of qualitative research is to explore the depth and nuances of a particular topic. So you’ll be engaged with uncovering it through words and detailed descriptions, rather than hard numbers. A qualitative study sees data being presented primarily in the form of words , often supplemented with quantitative data that supports relevant claims. You’re likely to resort to this kind of analysis if you’re working in humanities and social sciences. 

The first decision you’ll need to make at this moment is whether you’ll be structuring your data chronologically (in order of how you conducted the research) or thematically (in terms of patterns and trends that you see in your data). 

Ensure that each finding you highlight is directly relevant to your research question. You may have made many discoveries over the course of your research, but your chapter has to be concise and report findings that either support or contradict your hypothesis. There is a lot of raw data that you will need to sift through to decide what’s important. 

Include excerpts and quotations from appropriate sources such as interviews, discussion transcripts, supporting literature, and so on, to back each of your findings. 

Although your chapter is mostly just a barrage of words, it’s useful to have graphs, tables, charts, and other visual elements that illustrate what you’re saying in text. Having such quantitative parameters within the chapter is not mandatory (and may not even apply to certain types of research, like a literary analysis), but is often helpful with establishing a story for your research. 

Commonly used qualitative research methods: in-depth interviews, case studies, focus group discussions, theoretical research , literary analysis, and so forth. 

Reporting quantitative research

Quantitative research, as the name suggests, focuses on studying data through statistical and mathematical techniques. If you’re doing this type of research for your dissertation, your results chapter will be dominated by statistics and numbers (represented through graphs, tables, charts, etc.), explained succinctly through text. 

Here’s what you have to include in the chapter: 

• Statistical analysis, their relevance and relationship with the research question 
• Observations about whether data supports or rejects the hypothesis 
• Trends, patterns, and relationships that can be understood from the data 

Since numerical data can be dense and difficult to understand at the first glance, it’s always advised that you articulate them visually, through graphs, tables, charts, and perhaps even relevant figures. Not only does this allow you to deconstruct data in a more appealing way, but it also allows you to spell out a narrative for your data, which you will support with text that explains your findings. 

Commonly used quantitative research methods: Surveys, polls, simulations and modeling of data 

Tips to write a good results section

• Include tables, figures, and other visual elements to present complex data in a more accessible way. These elements should supplement the words rather than be repetitive. 
• Use a variety of visual elements to illustrate data that might be difficult to interpret solely with words. 
• Be honest in your reporting. This may seem obvious, but it’s easy to forget that results always don’t need to corroborate your hypothesis. In fact, it’s perfectly acceptable for the opposite to happen; this is useful in telling the research community that something doesn’t work! What matters in this section is relevance.
• Be concise and precise in your reporting. You don’t need to delve into every little detail about your data. Simply present data and information that is relevant to your research question. 

Frequently Asked Questions

Are the results and discussion sections the same, do i have to combine the results and discussions sections, where can i document raw data i haven’t been able to include in the chapter, how long should the results section of a dissertation be, what can i include in an appendix.

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How To Analyze Survey Data For A Research Paper?

This post provides some tips and information about the process of analyzing survey data. Some of it is from Dave’s vlog and some of it is my own. Just a note about survey research.

Surveys can be quantitative with all questions/items that can be analyzed statistically or it can be mainly or in part qualitative. Qualitative research using a survey would include open-ended questions that the respondent has to write out in sentences or paragraphs. This post mainly addresses issues in quantitative survey research.  If you need help on writing a paper or editing your thesis, you should check out this detailed post.

A disclaimer about Dave’s vlog on this topic: This is one of Dave’s more technical vlogs, and you do have to have some baseline knowledge of research analysis methods to benefit from some of the content, but Dave did provides a great summary of key things that are important to keep in mind as you design your survey research and prepare to analyze survey data, whether is be more a smaller class project or your dissertation. You can view Dave’s full vlog here: 

First of all, before you begin your analysis, you must think about your research question and how the survey / questionnaire relates to your research question. How are you going to operationalize the variables specified in your research question? That is, how is the survey data going to describe phenomena that you are interested in observing and measuring? Also, if you made some hypotheses, how are you going to determine whether they are confirmed or rejected by the data? 

This post was written by Stephanie A. Bosco-Ruggiero (PhD candidate in Social Work at Fordham University Graduate School of Social Service) on behalf of Dave Maslach for the R3ciprocity project (Check out the YouTube Channel or the writing feedback software ). R3ciprocity helps students, faculty, and research folk by providing a real and authentic look into doing research. It provides solutions and hope to researchers around the world.

Creating a data analysis plan

Specifically focus on your research questions before you do anything else and come up with a data analysis plan. If your research is purely quantitative (no open ended questions requiring content analysis) outline the statistical procedures you are going to use to answer your research question. Do you want to use bivariate or multivariate analyses? That is, do you want to measure the association between two variables, or do you want to observe how more than two variables impact an outcome or relate to each other? Some common bivariate analyses are Pearson chi-square or bivariate correlation. For a more rigorous multivariate analysis you might use a multiple linear regression or a cluster analysis. 

There is a lot of regression analysis to cover, so we are not going to cover regression here. People spend many courses trying to understand regression analysis. Most of it is thinking about how regression assumptions do and do not hold.

Avoiding confirmation bias

The key thing is to specify as much of the analysis before you touch the data. Why, you ask? We have a tendency as humans to look to confirm our hypotheses, and the goal in science is to objectively confirm or reject (falsify) your hypotheses. By specifying as much of the analysis upfront as possible, you prevent yourself from being human and selecting analytical methods that will more likely confirm your hypothesis as you proceed through your research.

Now, sometimes you do have to adjust your data analysis plan (more about that at the end) and that is ok in some instances, but don’t change your research questions and data analysis plan continuously as you go through your research because you want to come up with some kind of predetermine finding or don’t like what you’ve come up with your original plan.  

(This is Dave: Personally, I think you are OK to adjust as you go as long as you are upfront and clear with this in your analysis. If anyone has gone through the review process of a major journal, you will know that revise and improving clarity is a major part of writing papers. Yes, we know that there is debate about HARKing and such right now, but writing a paper is virtually impossible to do without this trial and error process. If we knew what the answer was upfront, which is what pre-specification presumes, then it would not be research.)

This pitfall of wanting to change our questions or plan to find something interesting or confirm our hypotheses is known as confirmation bias. We all want to find something interesting in our data, and all the better if our analyses confirm what we thought would happen, but we can’t will our results. They are what they are. By creating a data analysis plan early on, you are more likely to stick to it and not make too many adjustments based on what you’re seeing in the data, or learning, along the way. At some point, you just have to say, I will find what I find even if it’s not that interesting.

Here are tips Dave shared about things you should think about and steps you should take as you go through the process of planning your study and analyzing your data. 

• Consider construct validity. First you want to ask yourself whether your survey items are measuring your concept precisely enough. That is, is your main idea and hypothesis being accurately measured by the set of questions in your survey tool? If you adjust your hypotheses along the way, you may want to consider using a different survey tool if your original tool no longer measures the concept you are studying. To determine construct validity you want to become familiar with past studies and tools used to analyze and observe your key ideas or research question. Read more about construct validity here .
• Run your frequencies and plot your data. So you’ve gathered 100 completed surveys and you have them in hand or the data online. After you enter the data into a data analysis software platform (e.g. R, SAS, SPSS), run your frequencies. Simply look at your numbers. Can you glean anything from the descriptive data? Is there an imbalance in who answered your survey (e.g. by gender). Just take a look at the data and become familiar with the raw results. You can plot your continuous data as well. Dave says, “Always plot the data!” Try to think about simple histograms or scatterplots (x-y plots), or line plots. Then look at the data and see what it’s telling you. Take a look at the outliers and anomalies that show up in the data. Plotting allows you to see how the data lines up comparatively to what you would expect to see. 
• Explore your data. In order to run certain statistical tests, your data has to be appropriate for that test. First think about the basics. If your data is categorical (e.g. colors, states) you can’t run tests that are appropriate only for continuous variables (e.g interval or ratio data). You also need to confirm that your continuous data is appropriate for certain tests. Is it normally distributed? Does it contain numerous outliers? Learn about the requirements for running an ANOVA, regression, chi-square, etc. Then you have to decide which are your independent and dependent variables. If you are doing multivariate analyses, carefully consider which independent variables you want to include in the model. Also, do you want to create any interaction variables? Which control variables do you want to include so you can clearly understand which independent variables cause your dependent variable to vary. 

4. Run your analyses. Run your bivariate and/or multivariate analyses. When conducting a multiple linear regression, use a stepwise regression so you can add variables to the model one by one. If you remove or add a variable, do your findings suddenly become significant. Think about why this might be. A particular variable might also make your model unstable. Figure out which variable is causing the problem, and find out why. Is it intercorrelated with another variable? It’s ok to run a bunch of analyses that you never report on (Dave: Maybe. We always have to be clear on what we report on and don’t run. It’s just far more efficient use of your time to document, document, document.)

You just want to become familiar with your data and various results. If you want to run a bunch of bivariate analyses to become familiar with what you are going to see in your multivariate analyses, go right ahead. It doesn’t mean you have to report on every single test you run. Also, you are not deviating from your analysis plan by running more tests than you need. You are only deviating from your plan if you keep changing the variables you are looking, make a major change to your research methodology, or completely change the focus of your study or how you are going to analyze your data (e.g. scrapping a regression analysis plan to do a factor analysis, moving from a cross sectional analysis to a longitudinal study). 

5. If you conduct a one way ANOVA or regressions, run a post hoc analysis . If you find a difference in means between your variables, find out where the significant differences are. To do this run a post-hoc test , also known as a multiple comparisons test. For example, if you have groups of freshman, sophomore, and junior high school students taking a standardized test, and your ANOVA results are significant, run a post-hoc test to determine if all three groups have significantly different scores or whether the different lies between two specific groups. You have to choose your post-hoc statistic carefully (e.g. think Tukey) based on the characteristics of your data. 

6. Double check your work and output. We have all made mistakes at one time or another in analyzing our data or interpreting our results. Double check everything you’ve done after you’ve run all of your analyses. Do some of the results seem really off, or the data is not performing as expected? Trace your steps and make sure you entered all of the correct variables and ran the right tests. You can even have a student assistant double check your work, or have a colleague look at any puzzling results. 

7. Think about how your findings are different or similar to other studies’ findings. You should have conducted a literature review in the study planning stages to find out who has studied your concept, or closely related concepts, prior, and what they discovered. Are you going to confirm past findings or try to refute them? What should you include or not include in the analysis? How many research questions should you have and have you made them straightforward enough that they are easily analyzed? Take a look at your frequencies and think about whether the data is lining up with what was found in previous studies.  

8. Continuously write up your results: Obviously, people from a range of disciplines read this blog, so we can’t describe exactly how you’re going to write up your results because there are different formatting requirements in each discipline. We can tell you, however, that whatever the format, you are going to need to understand and write up your results and interpret them in a discussion section (or something similar). As soon as you look at your output you can start writing notes about about what your’re seeing and what it might mean. How does it relate to prior finding in this area of research? If your hypothesis was rejected or the null could not be rejected, think about why. If you found something completely new that has not been found before in your field, discuss why at the present time or in your particular study these results might have come about. 

9. Leftover data. Dave advises that you don’t need to use all of the data in the survey in your analysis. Save some for future research. You don’t want to go overboard in reporting every single result. Stick to what you wanted to look at according to your research questions, hypotheses, and data analysis plan. Of course, dissertation data and analyses can provide the perfect content for several peer reviewed research manuscripts (journal articles). Save all of your data!  (Dave: Indeed, a good research project should have room for 3 to many more studies with the data).

10. Think about future studies. What did you find that was particularly interesting from your data that you might want to explore further. Jot down some ideas for future studies that look at different angles of what you studied or that take your research to the next level. You might look at a similar set of research questions using a different research methodology or set of tests, or you might focus in on particular finding and explore it using qualitative survey techniques (e.g. focus groups, interviews.) 

Check out Dave’s vlog about Mistakes most PhDs make in their Doctoral Research and Scientific Careers: 

Here are a few more tips to consider as you conduct your quantitative survey research: 

• Keep careful track of who you administered your questionnaire to (create IDs for anonymity), if you changed any items along the way, and your process for distributing your survey. You’ll have to write all of this up later on. 
• Don’t forget about Ethics Approval! Every university and research institution has an Ethics Board or IRB. It is super important that you do that before you start doing research. Our research has consequences, some of them can be rather nasty, and we have to think about what those consequences are. If you need help, check out this video on the IRB Approval process:
• Be upfront about the limitations of your research. Don’t try to hide the limitation. Any good study disclosed limitations so the reader understands where there may be a lack of validity or reliability in the numbers. For example, if you have a small sample or it is skewed in some way, note that. You want your reader to understand whether these results might be similar for a different population. 
• If you don’t actually find much that is interesting or all of your hypotheses must be rejected, don’t despair, you are not the only one. Report your results and if you’ve done a good job you will get a good grade or your degree. Journals are full of studies that found nothing significant and nothing particularly interesting. (Dave: Yes and No. You have to think about why that is interesting to not find results.) This is research too and others in your field will learn from your results. Your results might even help you come up with a new theory. As Dave says, “That is the beauty of science….don’t be afraid to explore different avenues, you should be writing down and clear about the stuff you’ve done, be very systematic.” He also advised that a spurious result can be really interesting. 
• If you do need to change your data analysis plan, that is ok. As long as your new plan is helping you come up with results that best explain your research questions that is fine. You do have to write up a new data analysis plan and stick to your new plan, don’t keep changing it up. It’s great if you can stick to your original plan, but that often does not happen. 
• Do keep a codebook. A codebook is your menu of variables, their names, and their numerical codes. You should include all of your created interaction variables.  Also keep careful note or  log of all of your recoded variables and their new responses and codes. You will thank yourself later…..
• Did you benefit from this post? Do you know of anyone at all that could use feedback on their writing or editing of their documents? I would be so grateful if you read this post on how to get feedback on your writing using R3ciprocity.com or let others know about the R3ciprocity Project. THANK YOU in advance! You are the bees knees.

If you enjoyed this blog, check out these other blogs on r3ciprocity.com: 

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• How to Write a Results Section | Tips & Examples

How to Write a Results Section | Tips & Examples

Published on 27 October 2016 by Bas Swaen . Revised on 25 October 2022 by Tegan George.

A results section is where you report the main findings of the data collection and analysis you conducted for your thesis or dissertation . You should report all relevant results concisely and objectively, in a logical order. Don’t include subjective interpretations of why you found these results or what they mean – any evaluation should be saved for the discussion section .

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Table of contents

How to write a results section, reporting quantitative research results, reporting qualitative research results, results vs discussion vs conclusion, checklist: research results, frequently asked questions about results sections.

When conducting research, it’s important to report the results of your study prior to discussing your interpretations of it. This gives your reader a clear idea of exactly what you found and keeps the data itself separate from your subjective analysis.

Here are a few best practices:

• Your results should always be written in the past tense.
• While the length of this section depends on how much data you collected and analysed, it should be written as concisely as possible.
• Only include results that are directly relevant to answering your research questions . Avoid speculative or interpretative words like ‘appears’ or ‘implies’.
• If you have other results you’d like to include, consider adding them to an appendix or footnotes.
• Always start out with your broadest results first, and then flow into your more granular (but still relevant) ones. Think of it like a shoe shop: first discuss the shoes as a whole, then the trainers, boots, sandals, etc.

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If you conducted quantitative research , you’ll likely be working with the results of some sort of statistical analysis .

Your results section should report the results of any statistical tests you used to compare groups or assess relationships between variables . It should also state whether or not each hypothesis was supported.

The most logical way to structure quantitative results is to frame them around your research questions or hypotheses. For each question or hypothesis, share:

• A reminder of the type of analysis you used (e.g., a two-sample t test or simple linear regression ). A more detailed description of your analysis should go in your methodology section.
• A concise summary of each relevant result, both positive and negative. This can include any relevant descriptive statistics (e.g., means and standard deviations ) as well as inferential statistics (e.g., t scores, degrees of freedom , and p values ). Remember, these numbers are often placed in parentheses.
• A brief statement of how each result relates to the question, or whether the hypothesis was supported. You can briefly mention any results that didn’t fit with your expectations and assumptions, but save any speculation on their meaning or consequences for your discussion  and conclusion.

A note on tables and figures

In quantitative research, it’s often helpful to include visual elements such as graphs, charts, and tables , but only if they are directly relevant to your results. Give these elements clear, descriptive titles and labels so that your reader can easily understand what is being shown. If you want to include any other visual elements that are more tangential in nature, consider adding a figure and table list .

As a rule of thumb:

• Tables are used to communicate exact values, giving a concise overview of various results
• Graphs and charts are used to visualise trends and relationships, giving an at-a-glance illustration of key findings

Don’t forget to also mention any tables and figures you used within the text of your results section. Summarise or elaborate on specific aspects you think your reader should know about rather than merely restating the same numbers already shown.

Figure 1: Intention to donate to environmental organisations based on social distance from impact of environmental damage.

In qualitative research , your results might not all be directly related to specific hypotheses. In this case, you can structure your results section around key themes or topics that emerged from your analysis of the data.

For each theme, start with general observations about what the data showed. You can mention:

• Recurring points of agreement or disagreement
• Patterns and trends
• Particularly significant snippets from individual responses

Next, clarify and support these points with direct quotations. Be sure to report any relevant demographic information about participants. Further information (such as full transcripts , if appropriate) can be included in an appendix .

‘I think that in role-playing games, there’s more attention to character design, to world design, because the whole story is important and more attention is paid to certain game elements […] so that perhaps you do need bigger teams of creative experts than in an average shooter or something.’

Responses suggest that video game consumers consider some types of games to have more artistic potential than others.

Your results section should objectively report your findings, presenting only brief observations in relation to each question, hypothesis, or theme.

It should not  speculate about the meaning of the results or attempt to answer your main research question . Detailed interpretation of your results is more suitable for your discussion section , while synthesis of your results into an overall answer to your main research question is best left for your conclusion .

I have completed my data collection and analyzed the results.

I have included all results that are relevant to my research questions.

I have concisely and objectively reported each result, including relevant descriptive statistics and inferential statistics .

I have stated whether each hypothesis was supported or refuted.

I have used tables and figures to illustrate my results where appropriate.

All tables and figures are correctly labelled and referred to in the text.

There is no subjective interpretation or speculation on the meaning of the results.

You've finished writing up your results! Use the other checklists to further improve your thesis.

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

In qualitative research , for each question or theme, describe:

• Recurring patterns
• Significant or representative individual responses
• Relevant quotations from the data

Don’t interpret or speculate in the results chapter.

Results are usually written in the past tense , because they are describing the outcome of completed actions.

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

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Dissertation Results Section With Examples

Students studying MBA or Ph.D. courses from the college university of the UK face difficulty in writing the results section for a dissertation. The student has confusion related to the elements that they should include in the result, discussion, and conclusion section.  They face issues in identifying the proper format for presenting their findings in the dissertation.

Considering the issues faced by students’ the Expert team of UK Assignment help has helped the student in getting information about the way of writing the results section. They have also provided detail about the things students should consider while writing the results section.

After completion of the data collection and analysis procedure, you are required to write the result. It is an important section in the dissertation where you need to present your dissertation findings. Now students have queries related to things that should be included in the results section, so below is the answer to your question.

Elements of result section in the Dissertation

The results section is written for the dissertation and only includes the main findings of the investigation. The findings basically involve:

Information present in charts, graphs, tables. Contextualization of information. Explanation of the meaning of data. Important information related to participants or respondents. Key information related to research questions. Findings are drawn by analyzing the information gathered through secondary sources.

After knowing the things to be included in the results section, let’s look at the way of writing the results section for the dissertation.

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How do write results and discussion sections in the research paper?

You should also consider the type of study you have done before writing the results section. The structure of the results section while writing research papers is completely based on the field of investigation.

Review of guideline

Before writing the results section for the dissertation, It is very much important for you to review the guidelines provided by your tutor.  The guideline will help you in determining the things which you need to include in your results section.

While reviewing the guidelines, you should focus on the limitation and length of content to be included in the results section. Through reading the guideline, you will be able to judge the expectation of the reader from the specific section.

Think about your own research result

• It is a phase where you need to mainly emphasize outcome and findings which is related to your research questions. While writing the results section for your dissertation, you need to give subheadings for streamlining the report. It is the trick by applying that you can enable the reader to develop an understanding of the findings of the investigation.
• It is the phase where you need to pre-determine the structure of the results section for the dissertation.  You can organize the results section on the basis of research questions or hypotheses. Either hierarchical or chronological order can be used for structuring the results section.

Tips : While making the choice of structure for the results section you are required to keep in mind three things these are objectives, evidence, and audience.

  Create tables and figures for the presentation of information

You should properly number the tables and figures. Data included in the table should be self-descriptive. You should include important and complete information in tables. Figures and tables should be presented in such a manner that the reader by analyzing them can develop an understanding of the findings of the research.

Write the results section by utilizing figures and findings

the main purpose of the third stage is to present the complex data in a proper manner.

While writing the results section, in the first paragraph you need to mainly emphasize relating the objectives of the investigation or research questions to the findings. You should put effort into writing the results section for your dissertation in the past tense.

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In addition to this, you can also provide a summary of important findings after the completion of the results section. It is the technique that will help you in creating the transitions between the interpretation and discussion section of the dissertation.

Students need to define the abbreviation or complex terms used in the findings.

Revision and editing

After completion of the results section, you should review it. As reviewing technique will help you in the identification of errors or misinterpretation of information.

While making a revision, proofreading, and editing the results section you are required to ensure that research results are presented in a systematic manner. You should also revise the objectives, aim, and introduction, and should confirm that your research results are accurate.

Tip:  You should maintain consistency in presenting your research results.

While reviewing the results you can read loudly the content. It is the technique while it will help you in the identification of small errors which can further have a great influence on results. You can seek help from other people for checking the results section.

Let,s look at an example which will help you in developing an in-depth understanding of the writing results section for the dissertation.

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Dissertation results section example

Example: An investigation is being performed to analyze whether women prefer to read a romantic novel as compared to men.  In this investigation the independent variable is gender and the dependent variable is assumption related to the reading of books.

As gender is categorized into two categories that are male and female. Therefore, it is also recognized as a categorical variable.  The findings of the research can be presented using tables and graphs. You can present detailed information about the number of women who prefer to read Romantic novels.

Now, let’s look at the way of presenting the Quantitative results in a dissertation.

How do present Quantitative results?

One of the best techniques that can be utilized to present the research findings or outcome is to design them considering the research questions. After that, you are required to present research findings for every subsection.

You should also include statistical analysis that has been performed for analyzing the results. It is very much essential for you to analyze whether the research findings of all the sections are relevant to the research questions.  While presenting the outcomes you can mark the key trends, the relationship between data, etc.

Below is an example of presenting the Quantitative result. By seeing the example you will get an idea about presenting the  Quantitative result.

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Example: Quantitative dissertation results section 

For instance, an investigation was performed on Fashion companies. The main objective of executing the investigation is to assist the company in the identification of the latest trends related to clothing.  Market research or survey has been conducted for collecting information about the same. Findings of research reveal that there is a great demand for ethnic wear clothes in the market

After completion of an investigation while presenting the research results you can include the responses provided by people. You can highlight the key clothing trends in the market.  You can include graphs or charts for presenting the difference in choices of clothes among people over a period of time. Tables, graphs, charts, etc can be useful and helpful for presenting complex data.

Note: If in case the research findings are not at all relevant to the questions then in such a situation you can include extra information in the Appendix.

The regression analysis technique is utilized for testing the first hypothesis related to market demand. In the above example, fashion trends are an independent variable, and market demand is the dependent variable. The research findings reveal that changes in trends have a great influence on market demand for specific types of clothes.

The outcome of regression analysis

Now, after gaining an understanding of the presentation of quantitative results. Let us look at how we could present Qualitative results.

Qualitative findings and analysis dissertation example 

In relation to the qualitative investigation, the research findings might not be directly relevant to the research questions. Therefore, you need to organize your results section in the dissertation section according to the themes. In simple words, you can utilize the thematic analysis techniques for presenting your findings.

You can prepare the theme on the basis of research questions and answers provided by respondents. The thematic analysis helps you in analyzing the pattern of the way responses are provided by participants. While presenting the research findings you can include quotes as evidence for supporting the points. For instance, you can include a complete transcript of an interview in the appendix.

Presentation of Qualitative findings

Example: An investigation was performed for analyzing the view of people about video games as art. The research findings indicate that the majority of respondent perceives that video game is not a form of art. Some participants have stated that creativity is there in the creation of video games.

A statement given by one of the respondents is that I think the producer of video games has utilized their creative skills for designing video games and including different features in them. The fact which has been concluded from the investigation is that many people believe that video games are more artistic.

Often students get confused about the things to be included in a discussion, conclusion, and results section. They include interpretations and observations in the discussion which is wrong. It is very much important for students to gain knowledge about the difference between the result, discussion, and conclusion section. below the difference between all three has been discussed. The things you should include in the discussion, conclusion, and results section have been highlighted.

Results Vs discussion VS. conclusion section in the project report

 Results section:  The results section in the dissertation includes the findings of the investigation. It only includes detailed information about observations in the context of Questions. The Results section in the dissertation does not include complete answers to key research questions. While writing the results section for a dissertation, you should not utilize words such as implies, suggest, etc. As all such words are more appropriate for writing the discussion section.

Discussion section:  The discussion section in the dissertation includes the interpretation of the research results. In the discussion section of the dissertation, you need to relate your research outcomes with the literature review . You are also required to include the limitations of your study and the importance of research findings.

The results and discussion section in the project report are very important parts. A discussion on the result section helps the researcher in reaching the solution.

Conclusion section : The conclusion part of the dissertation consists of a summary of key research findings. It includes the complete answers to all research questions.

Below are a few tips which you can apply while presenting the research findings in the results section for the dissertation. These tips will help you in writing the results section in a proper manner.

Tips for writing a Results section for the dissertation

Here, are a few tips that you can utilize for writing the results section for the dissertation in a proper manner.

• Before writing the results section you are required to consider things that you need to focus such as aim, objectives, and research questions. While writing the results section you need to relate your findings with the research questions or objectives of the investigation.
• You can make use of graphs, tables, charts, etc. for presenting information in a systematic manner.
• After writing the results section you are required to ensure that research findings are presented in a logical and systematic manner. One best technique for organizing your results section is to write themes, then a table containing the data, then a graph, and finally an interpretation of information.

While presenting the research finding in the results section, you should understand that tables and graphs are important components of the results section. Therefore, you should provide a proper caption for tables and figures.

Now, along with tips let us look at certain considerations that should make while writing the results section.

Key considerations while writing dissertation results 

 A few things which you  should consider writing the results section are:

• You should consider the main variables of your study.
• It is important to note that Quantitative research involves at least one independent and dependent variable. In the results section, you should define the variables of your study clearly. The dependent variable is considered to be an outcome variable. Independent variables are those which are controlled by the researcher. It is controlled by an investigator for testing its influence on dependent variables.
• Another essential thing you are required to consider is whether variables in your study are continuous or categorical. In simple words, you need to determine the relationship between both the dependent and independent variables.
• Continuous variables are those which keep changing with the passage of time or situation.
• The categorical variable is those variables that have fixed values.
• Now, after getting knowledge about the things we should consider, let’s develop an understanding of the procedure for the composition of the results section

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Writing up the results section of your dissertation

(Last updated: 12 May 2021)

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When asked why doing a dissertation can be such a headache, the typical student usually replies with one of two answers. Either, they simply don't like writing enormous volumes of text, or – and you may relate here – they categorically do not enjoy analysing data. "It's so long and boring!", the typical student wails.

Well, students wail, and we answer. We have put together this very comprehensive, very useful guide on how to write up the results section of your dissertation. To help you further, we've broken the information down into both quantitative and qualitative results, so you can focus on what applies to you most.

Writing up your quantitative results

Understanding the basics of your research.

First, you need to recall what you have assessed – or what your main variables are.

All quantitative research has at least one independent and one dependent variable, and, at this point, you should define them explicitly. An independent variable is one that you control to test its effects on the dependent variable. A dependent variable is thus your outcome variable.

Second, you need to determine if your variables were categorical or continuous.

A categorical variable is one with a fixed number of possible values, and a continuous variable is one where final scores have a wide range. Finally, you need to recall if you have used a so-called covariate or confounder variable. This is a variable that could have influenced the relationship between your independent and dependent variable, and that you controlled in order to accurately estimate the relationship between your main variables.

Let’s explain all this with an example. Suppose that your research was to assess whether height is associated with self-esteem. Here, participants’ height is an independent variable and self-esteem is a dependent variable. Because both height and scores on a measure of self-esteem can have a wide range, you have two continuous variables. You might have also wanted to see if the relationship between height and self-esteem exists after controlling for participants’ weight. In this case, weight is a confounding variable that you need to control for.

Here is another example. You might have assessed whether more females than males want to read a specific romantic novel. Here, your independent variable is gender and your dependent variable is the determination to read the book. Since gender has categories (male and female), this is a categorical variable. If you have assessed the determination to read the book on a scale from 1 to 10 (e.g. 1 = no determination at all to read the book, all the way to 10 = extremely strong determination to read it), then this is a continuous variable; however, if you have asked your participants to say whether they do or do not want to read the book, then this is a categorical variable (since there are two categories: “yes” and “no”).

Lastly, you might have wanted to see if the link between gender and the determination to read the book exists after controlling for participants’ current relationship status. Here, relationship status is your confounding variable.

We will return to these examples throughout this blog post. At this point, it is important to remember that outlining your research in this way helps you to write up your results section in the easiest way possible.

Let’s move on to the next step.

Outlining descriptive and frequencies statistics

In order to report descriptive and/or frequencies statistics, you need to outline all variables that you have used in your research and note whether those variables are continuous or categorical.

For continuous variables, you are using descriptive statistics and reporting the measures of central tendency (mean) and measures of variability or spread (standard deviation). For categorical variables, you are using frequencies statistics and reporting the number (or frequency) of participants per category and associated percentages. Both these statistics require you to make a table, and in both cases you also need to comment upon the statistics.

How does all of this look in practice? Recall the two examples that were outlined above. If you have assessed the association between participants’ height and self-esteem, while controlling for participants’ weight, then your research consists of three continuous variables. You need to make a table, as in TABLE 1 below, which identifies means and standard deviations for all these variables. When commenting upon the results, you can say:

Participants were on average 173.50 cm tall (SD = 5.81) and their mean weight was 65.31 kg (SD = 4.44). On average, participants had moderate levels of self-esteem (M = 5.55, SD = 2.67).

Note that, in this example, you are concluding that participants had moderate self-esteem levels if their self-esteem was assessed on a 1 to 10 scale. Since the value of 5 falls within the middle of this range, you are concluding that the mean value of self-esteem is moderate. If the mean value was higher (e.g., M = 8.33), you would conclude that participants’ self-esteem was, on average, high; and if the mean value was lower (e.g., M = 2.44), you would conclude that average self-esteem scores were low.

Let’s now return to our second research example and say that you want to report the degree to which males and females want to read a romantic novel, where this determination was assessed on a 1-10 (continuous) scale. This would look as shown in TABLE 2.

We can see how to report frequencies statistics for different groups by referring to our second example about gender, determination to read a romantic novel, and participants’ relationship status.

Here, you have three categorical variables (if determination to read the novel was assessed by having participants reply with “yes” or “no”). Thus, you are not reporting means and standard deviations, but frequencies and percentages.

To put this another way, you are noting how many males versus females wanted to read the book and how many of them were in a relationship, as shown in TABLE 3. You can report these statistics in this way:

Twenty (40%) male participants wanted to read the book and 35 (70%) female participants wanted to read the book. Moreover, 22 (44%) males and 26 (52%) females indicated that they are currently in a relationship.

Reporting the results of a correlation analysis

The first of these is correlation, which you use when you want to establish if one or more (continuous, independent) variables relate to another (continuous, dependent) variable. For instance, you may want to see if participants’ height correlates with their self-esteem levels.

The first step here is to report whether your variables are normally distributed. You do this by looking at a histogram that describes your data. If the histogram has a bell-shaped curve (see purple graph below), your data is normally distributed and you need to rely on a Pearson correlation analysis. Here, you need to report the obtained r value (correlation coefficient) and p value (which needs to be lower than .05 in order to establish significance). If you find a correlation, you need to say something like:

One final thing to note, which is important for all analyses, is that when your p value is indicated to be .000, you never report it by saying “ p = .000”, but by noting “ p p = .011”.

If your data is skewed rather than normally distributed (see red graphs), then you need to rely on a Spearman correlation analysis. Here, you report the results by saying:

Spearman correlation analysis revealed a positive relationship between people’s height and their self-esteem (r s = .44, p There has been a significant positive correlation between height and self-esteem after controlling for participants’ weight ( r = .39, p = .034).

You also need to make a table that will summarise your main results. If you didn’t use a covariate, you will have a fairly simple table, such as that shown in TABLE 4. If you have used a covariate, your table is slightly more complex, such as that shown in TABLE 5. Note that both tables use “-” to indicate correlations that have already been noted within the table. Also note how “*”, “**”, and “***” are used to annotate correlations that are significant at different levels.

Reporting the results of a regression

These are the specific points that you need to address in order to make sure that all assumptions have been met:

(1) for the assumption of no multicollinearity (i.e., a lack of high correlation between your independent variables), you need to establish that none of your Tolerance statistics are below .01 and none of the VIF statistics are above 10;

(2) for the assumption of no autocorrelation of residuals (i.e., a lack of correlation between the residuals of two observations), you need to look at this table and see whether your Durbin-Watson statistic falls within a desirable range, depending on your number of participants and the number of predictors (independent variables); and,

(3) for the assumptions of linearity (i.e., a linear relationship between independent and dependent variables) and homoscedasticity (i.e., a variance of error terms that should be similar across the independent variables), you need to look at the scatterplot of standardised residual on standardised predicted value and conclude that your graph doesn’t funnel out or curve.

All of this may sound quite complex. But in reality it is not: you just need to look at your results output to note the Tolerance and VIF values, Durbin-Watson value, and the scatterplot. Once you conclude that your assumptions have been met, you write something like:

Since none of the VIF values were below 0.1 and none of the Tolerance values were above 10, the assumption of no multicollinearity has been met. Durbin-Watson statistics fell within an expected range, thus indicating that the assumption of no autocorrelation of residuals has been met as well. Finally, the scatterplot of standardised residual on standardised predicted value did not funnel out or curve, and thus the assumptions of linearity and homoscedasticity have been met as well.

If your assumptions have not been met, you need to dig a bit deeper and understand what this means. A good idea would be to read the chapter on regression (and especially the part about assumptions) written by Andy Field. You can access his book here . This will help you understand all you need to know about the assumptions of a regression analysis, how to test them, and what to do if they have not been met.

Now let’s focus on reporting the results of the actual regression analysis. Let’s say that you wanted to see if participants’ height predicts their self-esteem, after controlling for participants’ weight. You have entered height and weight as predictors in the model and self-esteem as a dependent variable.

First, you need to report whether the model reached significance in predicting self-esteem scores. Look at the results of an ANOVA analysis in your output and note the F value, degrees of freedom for the model and for residuals, and significance level. These values are shown in PICTURE 2.

Significance value tells you if your predictor reached significance – such as whether participants’ height predicted self-esteem scores. You also need to comment upon the β value. This value represents the change in the outcome associated with a unit change in the predictor . Thus, if your β value is .351 for participants’ height (predictor/independent variable), then this means that for every increase in height by 1 cm, self-esteem increases by .35. You need to report the same thing for your other predictor – that is, participants’ weight.

Finally, since your model included both height and weight as predictors, and height acted as a significant predictor, you can conclude that participants’ height influences their self-esteem after controlling for weight.

Reporting the results of a chi-square analysis

For instance, you would do a chi-square analysis when you want to see whether gender (categorical independent variable with two levels: males/females) affects the determination to read a book, when this variable is measured with yes/no answers (categorical dependent variable with two levels: yes/no).

When reporting your results, you should first make a table as shown in TABLE 3 above. Then you need to report the results of a chi-square test, by noting the Pearson chi-square value, degrees of freedom, and significance value. You can see all these in your output.

Finally, you need to report the strength of the association, for which you need to look at the Phi and Cramer’s V values. When each of your variables has only two categories, as in the present example, Phi and Cramer’s V values are identical and it doesn’t matter which one you will report. However, when one of your variables has more than two categories, it is better to report the Cramer’s V value. You report these values by indicating the actual value and the associated significance level.

Note that Cramer’s V value can range from 0 to 1. The closer the value is to 1, the higher the strength of the association. You can report the results of the chi-square analysis in the following way:

Reporting the results of a t-test analysis

Recall that you have previously outlined descriptive statistics for these variables, where you have noted means and standard deviations for males’ and females’ scores on the determination to read the novel (see TABLE 2 above). Now you need to report the obtained t value, degrees of freedom, and significance level – all of which you can see in your results output.

You can say something like:

Reporting the results of one-way ANOVA

In the t-test example, you had two conditions of a categorical independent variable, which corresponded to whether a participant was male or female. You would have three conditions of an independent variable when assessing whether relationship status (independent variable with three levels: single, in a relationship, and divorced) affects the determination to read a romantic novel (as assessed on a 1-10 scale).

Here, you would report the results in a similar manner to that of a t -test. You first report the means and standard deviations on the determination to read the book for all three groups of participants, by saying who had the highest and lowest mean. Then you report the results of the ANOVA test by reporting the F value, degrees of freedom (for within-subjects and between-subjects comparisons), and the significance value.

There are two things to note here. First, before reporting your results, you need to look at your output to see whether the so-called Levene’s test is significant. This test assesses the homogeneity of variance – the assumption being that all comparison groups should have the same variance. If the test is non-significant, the assumption has been met and you are reporting the standard F value.

However, if the test is significant, the assumption has been violated and you need to report instead the Welch statistic, associated degrees of freedom, and significance value (which you will see in your output; for example, see PICTURE 3 above).

The second thing to note is that ANOVA tells you only whether there were significant differences between groups – but if there are differences, it doesn’t tell you where these differences lie. For this, you need to conduct a post-hoc comparison (Tukey’s HSD test). The output will tell you which comparisons are significant.

You can report your results in the following manner:

Reporting the results of ANCOVA

For instance, you will use ANCOVA when you want to test whether relationship status (categorical independent variable with three levels: single, in a relationship, divorced) affects the determination to read a romantic novel (continuous dependent variable, assessed on a 1-10 scale) after controlling for participants’ general interest in books (continuous covariate, assessed on a 1-10 scale).

To report the results, you need to look at the “test of between-subjects effects” table in your output. You need to report the F values, degrees of freedom (for each variable and error), and significance values for both the covariate and the main independent variable. As with ANOVA, a significant ANCOVA doesn’t tell you where the differences lie. For this, you need to conduct planned contrasts and report the associated significance values for different comparisons.

You can report the results in the following manner:

Reporting the results of MANOVA

For instance, you would use MANOVA when testing whether male versus female participants (independent variable) show a different determination to read a romantic novel (dependent variable) and a determination to read a crime novel (dependent variable).

When reporting the results, you first need to notice whether the so-called Box’s test and Levene’s test are significant. These tests assess two assumptions: that there is an equality of covariance matrices (Box’s test) and that there is an equality of variances for each dependent variable (Levene’s test).

Both tests need to be non-significant in order to assess whether your assumptions are met. If the tests are significant, you need to dig deeper and understand what this means. Once again, you may find it helpful to read the chapter by Andy Field on MANOVA, which can be accessed here .

Following this, you need to report your descriptive statistics, as outlined previously. Here, you are reporting the means and standard deviations for each dependent variable, separately for each group of participants. Then you need to look at the results of “multivariate analyses”.

You will notice that you are presented with four statistic values and associated F and significance values. These are labelled as Pillai’s Trace, Wilks’ Lambda, Hotelling’s Trace, and Roy’s Largest Root. These statistics test whether your independent variable has an effect on the dependent variables. The most common practice is to report only the Pillai’s Trace. You report the results in the same manner as reporting ANOVA, by noting the F value, degrees of freedom (for hypothesis and error), and significance value.

However, you also need to report the statistic value of one of the four statistics mentioned above. You can label the Pillai’s Trace statistic with V, the Wilks’ Lambda statistic with A, the Hotelling’s Trace statistic with T, and Roy’s Largest Root statistic with Θ (but you need report only one of them).

Finally, you need to look at the results of the Tests of Between-Subjects Effects (which you will see in your output). These tests tell you how your independent variable affected each dependent variable separately. You report these results in exactly the same way as in ANOVA.

Here’s how you can report all results from MANOVA:

Writing up your qualitative results

Before reporting the results of your qualitative research, you need to recall what type of research you have conducted. The most common types of qualitative research are interviews, observations, and focus groups – and your research is likely to fall into one of these types.

All three types of research are reported in a similar manner. Still, it may be useful if we focus on each of them separately.

Reporting the results of interviews

For example, let’s say that your qualitative research focused on young people’s reasons for smoking. You have asked your participants questions that explored why they started smoking, why they continue to smoke, and why they wish to quit smoking. Since your research was organised in this manner, you already have three major themes: (1) reasons for starting to smoke, (2) reasons for continuing to smoke, and (3) reasons for quitting smoking. You then explore particular reasons why your participants started to smoke, why they continue to smoke, and why they want to quit. Each reason that you identify will act as a subtheme.

When reporting the results, you should organise your text in subsections. Each section should refer to one theme. Then, within each section, you need to discuss the subthemes that you discovered in your data.

Let’s say that you found that young people started smoking because: (1) they thought smoking was cool, (2) they experienced peer pressure, (3) their parents modelled smoking behaviour, (4) they thought smoking reduces stress, and (5) they wanted to try something new. Now you have five subthemes within your “reasons for starting to smoke” theme. What you need to do now is to present the findings for each subtheme, while also reporting quotes that best describe your subtheme. You do that for each theme and subtheme.

It is also good practice to make a table that lists all your themes, subthemes, and associated quotes.

Here’s an example of how to report a quote within a text:

Reporting the results of observations

For instance, you might have noticed that the therapist finds it important to discuss: (1) the origin of the problem, (2) the lack of a patient’s medical difficulties, (3) the experience of stress, (4) the link of stress to the problem, and (5) the new understanding of the problem. You can consider these as themes in your observations.

Accordingly, you will want to report each theme separately. You do this by outlining your observation first (this can be a conversation or a behaviour that you observed), and then commenting upon it.

Here’s an example:

Therapist: Was there something that stressed you out during the last few months?

Patient: Yes, of course. I thought I would lose my job, but that passed. After that, I was breaking up with my girlfriend. But between those things, I was fine.

Therapist: And was there any difference in your symptoms while you were and while you were not stressed?

Patient: Hmmm. Actually yes. Now that I think of it, they were mostly present when I went through those periods.

Therapist: Could it be that stress intensifies your symptoms?

Patient: I never thought of it. I guess it seems logical. Is it?

Reporting the results of focus groups

As an example, let’s say that your focus group dealt with identifying reasons why some people prefer Coca-Cola over Schweppes, and vice versa. You have transcribed your focus group sessions and have extracted themes from the data. You have discovered a wide variety of reasons why people prefer one of the two drinks.

When reporting your results, you should have two sections: one listing reasons for favouring Coca-Cola, and the other listing reasons for favouring Schweppes. Within each section, you need to identify specific reasons for these preferences. You should connect these specific reasons to particular quotes.

Here’s an example of how this may look:

In conclusion…

As we have seen, writing up qualitative results is easier than writing quantitative results. Yet, even reporting statistics is not that hard, especially if you have a good guide to help you.

Hopefully, this guide has reduced your worries and increased your confidence that you can write up the results section of your dissertation without too many difficulties.

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How to Create a Survey Results Report (+7 Examples to Steal)

Do you need to write a survey results report?

A great report will increase the impact of your survey results and encourage more readers to engage with the content.

Create Your Survey Now

In This Article

1. Use Data Visualization

2. write the key facts first, 3. write a short survey summary, 4. explain the motivation for your survey, 5. put survey statistics in context, 6. tell the reader what the outcome should be, 7. export your survey results in other formats, bonus tip: export data for survey analysis, faqs on writing survey summaries, how to write a survey results report.

Let’s walk through some tricks and techniques with real examples.

The most important thing about a survey report is that it allows readers to make sense of data. Visualizations are a key component of any survey summary.

Examples of Survey Visualizations

Pie charts are perfect when you want to bring statistics to life. Here’s a great example from a wedding survey:

Pie charts can be simple and still get the message across. A well-designed chart will also add impact and reinforce the story you want to tell.

Here’s another great example from a homebuyer survey introduction:

If your survey is made up of open-ended questions, it might be more challenging to produce charts. If that’s the case, you can write up your findings instead. We’ll look at that next.

When you’re thinking about how to write a summary of survey results, remember that the introduction needs to get the reader’s attention.

Focusing on key facts helps you to do that right at the start.

This is why it’s usually best to write the survey introduction at the end once the rest of the survey report has been compiled. That way, you know what the big takeaways are.

This is an easy and powerful way to write a survey introduction that encourages the reader to investigate.

Examples of Survey Summaries With Key Facts

Here’s an awesome example of a survey summary that immediately draws the eye.

The key finding is presented first, and then we see a fact about half the group immediately after:

Using this order lets us see the impactful survey responses right up top.

If you need help deciding which questions to ask in your survey, check out this article on the best survey questions to include.

Your survey summary should give the reader a complete overview of the content. But you don’t want to take up too much space.

Survey summaries are sometimes called executive summaries because they’re designed to be quickly digested by decision-makers.

You’ll want to filter out the less important findings and focus on what matters. A 1-page summary is enough to get this information across. You might want to leave space for a table of contents on this page too.

Examples of Short Survey Introductions

One way to keep a survey summary short is to use a teaser at the start.

Here’s an example introduction that doesn’t state all of its findings but gives us the incentive to keep reading:

And here’s a great survey introduction that summarizes the findings in just one sentence:

In WPForms, you can reduce the size of your survey report by excluding questions you don’t need. We decided to remove this question from the report PDF because it has no answers. Just click the arrow at the top, and it won’t appear in the final printout:

This is a great way to quickly build a PDF summary of your survey that only includes the most important questions. You can also briefly explain your methodology.

When you create a survey in WordPress, you probably have a good idea of your reasons for doing so.

Make your purpose clear in the intro. For example, if you’re running a demographic survey , you might want to clarify that you’ll use this information to target your audience more effectively.

The reader must know exactly what you want to find out. Ideally, you should also explain why you wanted to create the survey in the first place. This can help you to reach the correct target audience for your survey.

Examples of Intros that Explain Motivation

This vehicle survey was carried out to help with future planning, so the introduction makes the purpose clear to the reader:

Having focused questions can help to give your survey a clear purpose. We have some questionnaire examples and templates that can help with that.

Explaining why you ran the survey helps to give context, which we’ll talk about more next.

Including numbers in a survey summary is important. But your survey summary should tell a story too.

Adding numbers to your introduction will help draw the eye, but you’ll also want to explain what the numbers tell you.

Otherwise, you’ll have a list of statistics that don’t mean much to the reader.

Examples of Survey Statistics in Context

Here’s a great example of a survey introduction that uses the results from the survey to tell a story.

Another way to put numbers in context is to present the results visually.

Here, WPForms has automatically created a table from our Likert Scale question that makes it easy to see a positive trend in the survey data:

If you’d like to use a Likert scale to produce a chart like this, check out this article on the best Likert scale questions for survey forms .

Now that your survey report is done, you’ll likely want action to be taken based on your findings.

That’s why it’s a good idea to make a recommendation.

If you already explained your reasons for creating the survey, you can naturally add a few sentences on the outcomes you want to see.

Examples of Survey Introductions with Recommendations

Here’s a nice example of a survey introduction that clearly states the outcomes that the organization would like to happen now that the survey is published:

This helps to focus the reader on the content and helps them to understand why the survey is important. Respondents are more likely to give honest answers if they believe that a positive outcome will come from the survey.

You can also cite related research here to give your reasoning more weight.

You can easily create pie charts in the WPForms Surveys and Polls addon. It allows you to change the way your charts look without being overwhelmed by design options.

This handy feature will save tons of time when you’re composing your survey results.

Once you have your charts, exporting them allows you to use them in other ways. You may want to embed them in marketing materials like:

• Presentation slides
• Infographics
• Press releases

WPForms makes it easy to export any graphic from your survey results so you can use it on your website or in slides.

Just use the dropdown to export your survey pie chart as a JPG or PDF:

And that’s it! You now know how to create an impactful summary of survey results and add these to your marketing material or reports.

WPForms is the best form builder plugin for WordPress. As well as having the best survey tools, it also has the best data export options.

Often, you’ll want to export form entries to analyze them in other tools. You can do exactly the same thing with your survey data.

For example, you can:

• Export your form entries or survey data to Excel
• Automatically send survey responses to a Google Sheet

We really like the Google Sheets addon in WPForms because it sends your entries to a Google Sheet as soon as they’re submitted. And you can connect any form or survey to a Sheet without writing any code.

The Google Sheets integration is powerful enough to send all of your metrics. You can add columns to your Sheet and map the data points right from your WordPress form.

This is an ideal solution if you want to give someone else access to your survey data so they can crunch the numbers in spreadsheet format.

We’ll finish up with a few questions we’ve been asked about survey reporting.

What Is a Survey Report and What Should It Include?

A survey report compiles all data collected during a survey and presents it objectively. The report often summarizes pages of data from all responses received and makes it easier for the audience to process and digest.

How Do You Present Survey Results in an Impactful Way?

The best way to present survey results is to use visualizations. Charts, graphs, and infographics will make your survey outcomes easier to interpret.

For online surveys, WPForms has an awesome Surveys and Polls addon that makes it easy to publish many types of surveys and collect data using special survey fields:

• Likert Scale (sometimes called a matrix question )
• Net Promoter Score (sometimes called an NPS Survey)
• Star Rating
• Single Line Text
• Multiple Choice (sometimes called radio buttons )

You can turn on survey reporting at any time, even if the form expiry date has passed.

To present your results, create a beautiful PDF by clicking Print Survey Report right from the WordPress dashboard:

Next Step: Make Your Survey Form

To create a great survey summary, you’ll want to start out with a great survey form. Check out this article on how to create a survey form online to learn how to create and customize your surveys in WordPress.

You can also:

• Learn how to create a popup WordPress survey
• Read some rating scale question examples
• Get started easily with a customer survey template from the WPForms template library.

Ready to build your survey? Get started today with the easiest WordPress form builder plugin. WPForms Pro includes free survey form templates and offers a 14-day money-back guarantee.

If this article helped you out, please follow us on Facebook and Twitter for more free WordPress tutorials and guides.

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This is really good

Hi Jocasta! Glad to hear that you enjoyed our article! Please check back often as we’re always adding new content as well as updating old ones!

Hi, I need to write an opinion poll report would you help with a sample I could use

Hi Thuku, I’m sorry but we don’t have any such examples available as it’s a bit outside our purview. A quick Google search does show some sites with information and examples regarding this though. I hope that helps!

With the Likert Scale what visualisation options are available? For example if there were 30 questions… I would like to be able to total up for all questions how many said never, or often… etc… and for each ‘x’ option for example if it was chocolate bars down the side and never through to often across the top… for each question… I would like to total for all questions for each chocolate bar… the totals of never through to often…? can you help?

Hey Nigel- to achieve what you’ve mentioned, I’d recommend you to make use of the Survey and Poll addon that has the ability to display the number of polls count. Here is a complete guide on this addon

If you’ve any questions, please get in touch with the support team and we’d be happy to assist you further!

Thanks, and have a good one 🙂

I am looking for someone to roll-up survey responses and prepare presentations/graphs. I have 58 responses. Does this company offer this as an option? If so, what are the cost?

Hi Ivory! I apologize for any misunderstanding, but we do not provide such services.

Hi! Can you make survey report.

Hi Umay! I apologize as I’m not entirely certain about your question, or what you’re looking to do. In case it helps though, our Survey and Polls addon does have some features to generate survey reports. You can find out more about that in this article .

I hope this helps to clarify 🙂 If you have any further questions about this, please contact us if you have an active subscription. If you do not, don’t hesitate to drop us some questions in our support forums .

Super helpful..

Hi Shaz! We’re glad to hear that you found this article helpful. Please check back often as we’re always adding new content and making updates to old ones 🙂

Hi , can you help meon how to present the questionnaire answer on my report writing

Hi Elida – Yes, we will be happy to help!

If you have a WPForms license, you have access to our email support, so please submit a support ticket . Otherwise, we provide limited complimentary support in the WPForms Lite WordPress.org support forum .

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Microsoft 365 Life Hacks > Presentations > How to Present Survey Results

How to Present Survey Results

After you complete a survey, it can be difficult to tell a story with the data you gathered. Data storytelling needs to consider your audience, how to articulate findings, and data visualization tools that can make it happen. Whether it’s for a client or among your team, it’s important for your audience to understand your results and translate them into actionable decisions. Learn how to conduct presentations on survey results methodically, by relying on best practices and tools.

What Are the Best Ways to Present Survey Results?

To present survey results effectively, you need to utilize a combination of techniques, practices, and visuals to ensure clarity and engagement. Incorporate the following strategies in your presentation:

Tell your story with captivating presentations

Powerpoint empowers you to develop well-designed content across all your devices

Select an Appropriate Format

One of the first decisions to make when presenting survey results is selecting the appropriate format. Consider the preferences of your audience and the complexity of the data. Microsoft PowerPoint presentations succinctly summarize key findings in a digestible visual format, so your audience can engage with them. You can also explore other formats, like a written report or interactive dashboard, which also provides advantages for different audiences.

Visualize Your Data

The purpose of data visualization is to tell a story, making important data points compelling and easily understood by the audience. You can use charts, graphs, infographics , and diagrams to make your results understandable and appealing. Keep your audience and data in mind as you decide which data visualizations feel appropriate.

Know Your Audience

When crafting your presentation, it’s important to understand your audience so you can tailor the presentation’s delivery to their needs and understanding. Consider their background, expertise, and interests when preparing your presentation. Before the presentation, clarify any needs to ensure that your presentation meets expectations. The language and terminology you use should be appropriate for your audience; it’s important to avoid too much jargon or confusing technical terms.

Practice and Rehearse Your Presentation

When delivering presentations that share survey results, thorough practice and rehearsal is essential. You want to clearly articulate data points, build confidence in your presentation, and confirm that your presentation doesn’t exceed any existing time constraints. Additionally, you should prepare for potential questions from the audience, so that you’re not caught off guard at the end of the presentation. PowerPoint’s speaker notes can help you practice what to say without forgetting a key point.

Foster Audience Engagement

Finally, you should create opportunities for audience engagement. Encouraging questions, discussions, and feedback fosters collaboration and interaction. You can incorporate polls and direct questions to the audience to foster active engagement. Listening to input and addressing questions or comments can help you ensure a productive and meaningful presentation experience for everyone involved.

By employing these techniques and practices, you can conduct presentations on survey results that are informative, engaging, and actionable. With meticulous preparation and rehearsal, you can communicate survey results in way that drives actionable insights and decisions, while leaving a positive impression on your audience. For more ways to improve your data storytelling and visualization, learn more presentation tips .

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How to Present Survey Results

Having worked hard on your survey design and achieved some great results, you’ll want to maximise their value with those who matter.

While a downloadable or emailed survey report , is the more traditional way of presenting your survey results, there are better and more engaging ways. And one of the best of these is through a live, stand-up presentation.

Whether you’re presenting to employees or some other stakeholder group, communicating your survey results via a live presentation, helps drive greater engagement and collaboration. Subsequently, this can help to bring about better decision making and actions as a result.

However, before you do anything else, you need to think about the structure and delivery of your presentation, if you’re to best meet your aims. So, that’s what we’ll look at next.

Presentation structure

When it comes to the presentation and communication of survey results, some of the best results are possible when they are presented like a story.

Ultimately, when you create a survey , you will have an overall objective that you want it to achieve. You will also have some actions in mind that you will want your audience to take when you present your results to them.

So, by adopting the following presentation structure, you’ll be better able to communicate the key findings to your audience. This will also help enable them to take the most appropriate actions as a result.

What’s the most crucial issue?

Whether you’re trying to identify the key drivers influencing your employees’ engagement levels, or satisfaction among your customer audience.

Whatever burning question you’re trying to get answers to with your survey. By focusing on it and making it your key theme, you’re more likely to engage and grab your audience’s interest from the outset.

What does the data mean for your audience?

Besides thinking about how much detail you need to go into, you also need to consider the impact of your data findings on your audience.

While they will be keen to hear about your survey’s findings, they’ll be more interested to know how this might impact their work or life. So, do communicate what the data means for different audience groups and any subsequent changes you propose to make, when you’re presenting your survey results.

Communicate any actions you need your audience to take and the benefits of taking them

Whatever audience you’re presenting to, having outlined the data findings and conclusions from your research, it’s likely they’ll be actions you need them to take.

Whether it’s fresh activities you want staff to get involved in to increase their engagement, or new processes you need them to learn to improve customer support. Whatever the actions, these need to be communicated clearly, along with the wider benefits for staff and the organisation, to encourage their participation.

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Using visuals to bring your data to life

Besides your presentation’s structure, you also need to be thinking about the visual elements that will help bring your data and story to life.

Graphs and custom charts

When it comes to illustrating your survey findings, whether that’s statistics, a visual breakdown of how different groups answered a question, or a mix of both. Whatever it is, the use of graphs or custom charts such as bar, column, line, area or pie charts can really make it stand out. It can also make it more appealing and easier to read.

Putting the focus on numbers

Depending on your story, the data you need to communicate and the composition of your audience, you may want to put greater emphasis on hard numbers and statistics. This will certainly be the case if you’re presenting to many people in leadership roles, who will want to see hard quantifiable numbers in your presentation.

Besides the obvious methods of providing the number of respondents and percentages for responses, you should consider including some visible and tangible metrics.

For example, if you wanted to highlight levels of satisfaction among your customer base, then you may choose to illustrate this with dashboards for your customers’ NPS and CSAT scores. Alternatively, you could replace this with an eNPS dashboard, to get a better sense of how happy staff were working for your organisation (see our Employee Net Promoter Score calculator for an example).

Real-time visuals

You also need to think about the supporting visuals you can use to show live data results as they are coming in.

From PowerPoint and Google Presentations to Prezi and Empressr. There are a whole host of presentation tools available with features including animated gifs, which you can use to bring your presentation and data to life. Such tools are great for encouraging further collaboration and discussion among your audience.

Analysis of qualitative data

It doesn’t matter what you’ve been researching, at times you’ll want to look beyond the top-level stats and get more in-depth details about what people are actually saying.

Text analysis is an innovative and useful tool that enables you to do this.

When activated the text analysis feature allows you to comb through the text responses to open ended questions, to look for correlations or popular keywords that appear in respondents’ comments. Once gathered these can be displayed in a Word Cloud, making it simpler for your audience to examine and interpret. It also allows greater insights to be gleaned from the data.

Remember you’re delivering insight not just data

The key thing to remember when you’re presenting the findings of your survey, is that you’re there to deliver insight not just data.

Ultimately, you will have an overall objective that you’re looking to achieve and actions you want your stakeholders to take. And they’ll be more likely to do this with an interesting and engaging presentation of your findings.

By examining and incorporating some of the guidance we’ve offered in this blog piece, you’ll be better able to deliver what you and your stakeholders need.

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5 Examples of How to Present Survey Results to Stakeholders

When you’ve lovingly designed, built, and distributed your survey and responses start flooding in, it’s time to begin the process of sorting and analyzing the data you’ll be presenting to stakeholders.

Once you’ve weeded the unusable responses, begin recording relevant responses through your survey platform or in a spreadsheet. If you use survey software like CheckMarket , you can easily transfer data into visuals with pre-built reports and dashboards.

Decide your data groups. Was the survey just answering one over-arching question? Or do you have multiple areas covered? Represent each data group separately.

For each result, provide additional information such as why you conducted the survey, what questions you were trying to answer, how the results help businesses, and any surprising answers.

When you have the data separated, the next step is to identify and prioritize the information your stakeholders will most want to see.

Choosing the Right Data to Share

First things first: who is your audience? Is it your boss? Is it your peers? Is it your direct clients or customers? The information that clients want to see, for instance, may be completely different to what your boss is interested in. The information you choose to share will vary drastically depending on the campaign you’re working on.

For example, if you’re working on a new marketing campaign, your audience may be interested in how you plan on advertising your business and what perks that may bring them.

However, when it comes to your stakeholders, they will be less interested in the customer perks, and more interested in how this new campaign will work for the business. They might want to know:

• How is it going to grow your audience?
• How will it turn them from leads to paying customers?
• How can this help improve your business’s bottom line?

When you’re presenting results, clearly define the purpose of the survey and why it matters to your stakeholders. Your story should be specific and concise.

Raise vital questions early on and have the answers ready to go. Your stakeholders have a limited amount of time to listen to what you have to say – make sure you are making the most of it.

This means you’ll have to pick and choose your data results carefully. All results need to be relevant and essential. Your stakeholders will be interested in information that makes a difference. And you’ll want the answers to be presented in the easiest way possible – which is why you want to choose your display method carefully.

5 Ways to Display Your Survey Results

When you present results, you are looking to be clear, simple, and memorable. So, viewers should not have to ask you to explain your results.

Here are five common ways to present your survey results to businesses, stakeholders, and customers.

1. Graphs and Charts

Graphs and charts summarize survey results in a quick, easy graphic for people to understand. Some of the most common types of graphs include:

• Bar graphs are the most popular way to display results. Easily create, customize, and show results. Most people also know how to read a basic bar graph to interpret survey results.
• Line graphs show how results change over time by tracking the ups and downs of the data.
• Pie charts show the breakup of a whole into sections. For example, your whole could be the total number of respondents, and the sections represent percentages that answered a certain way.
• Venn diagrams show the interaction between respondents and their answers. For example, overlapping circles could show the differences and similarities in responses between parents who use a product versus non-parents who use a product.

When creating a chart or graph, make the findings clear to read. Avoid too many intersecting lines and text options. If you can’t fit all the information into one graph, create several graphs rather than making one complex chart. Using colors to differentiate groups is another way to make results easy to read.

2. Infographics

Infographics add a creative twist to otherwise bland charts and graphs. A good infographic will use images to enhance the message, not distract from the data.

One survey results presentation example is to use silhouettes of people to convey a percentage of the population instead of a bar graph. This image helps those who see it connect the statistic to real people.

A word cloud is a powerful way to display open-ended question responses graphically. As more people respond with a specific word, that word will appear in the cloud – emphasizing the most relevant answers.

3. Video and Animations

People spend over 100 minutes a day watching videos – which is why marketers have tapped into this strategic area for reaching an audience. Nearly 88% of marketers say video marketing yields a strong return.

A video is a powerful tool for presenting information, including the results of your survey. You can capture your audience’s attention with motion, sound, and colorful statistics to help them remember information and react accordingly.

If you present findings through video, be aware that sharing options will be limited to platforms that can play a video – such a blog posts, websites, and PowerPoint presentations. Also, creating a PDF of the findings for people to look over at their leisure is a helpful way to support a video presentation.

4. Spreadsheets

Spreadsheets like Excel are not visually appealing, but they work well for organizing large amounts of information to create a survey results report.

While an image or video works best on websites, sometimes you may need to add more information than can fit in one picture.

Suppose you wanted to provide stakeholders or business partners with a detailed look at the survey and all the responses. A spreadsheet will allow the freedom to display all the necessary information at once. You can still use attractive infographics to summarize the findings and a video to present the report along with the spreadsheet.

5. Interactive Clickable Results

Interactive results are a fun way to allow viewers to explore results. You can also organize the findings to help break up large amounts of information.

Interactive maps are a common way to display survey results graphically. For example, results can be viewed by region when they click on a specific map area. Interactive maps and displays work best for websites and blogs.

An infographic that summarizes all the data as a global average allows people who don’t have the time to explore the map to see the information.

Customize Your Results in One Place

Time is precious in the marketing industry. You don’t want to spend days analyzing and sorting through survey results.

And you don’t have to.

By using CheckMarket, you can create, gather, and present survey results with one easy-to-use platform.

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Watch CBS News

Trump and Biden's first presidential debate of 2024, fact checked

By Arden Farhi , Hunter Woodall , Jui Sarwate , Julia Ingram , Layla Ferris , Laura Doan , James LaPorta , Daniel Klaidman , Alexander Tin , Pete Villasmil, Sierra Sanders

Updated on: June 28, 2024 / 9:46 AM EDT / CBS News

Here's the fact check of some of the statements made by President Biden and former President Donald Trump during the first 2024 presidential debate , which took place in Atlanta on Thursday, June 27. The two tangled on topics including immigration, the economy, abortion and their respective records. Mr. Biden seemed to ramble during many of his responses.

CBS News  covered the debate live as it happened . 

Trump claims "we had the greatest economy in the history of our country": False

Trump : "We had the greatest economy in the history of our country. And we have never done so well. Every- everybody was amazed by it. Other countries were copying us." 

Details : Trump's claim is false that during his presidency the U.S. had the greatest economy in the history of the country by many of the common metrics used to judge economic performance. The claim struggles when looking at GDP. If the 2020 pandemic  is excluded, growth after inflation under Trump averaged 2.49%, according to figures from the  World Bank . This is far from the GDP growth under Democratic President Bill Clinton of 3.88%, according to  World Bank data . Including the time period after COVID spread, that average drops to 1.18%. 

Trump's claim also falls short when compared to historical figures. Growth between 1962 to 1966 ranged from 4.4% to 6.6%. In 1950 and 1951, GDP ranged between 8.7% and 8%.

Under Mr. Biden, annual GDP growth is averaging 3.4%, according to the  Associated Press .

*An earlier version of this fact check misstated World Bank figures for growth after inflation under Trump at 2.65%, rather than 2.49%, and 1.45%, instead of 1.18%, and also rounded the growth number for Clinton. This has been updated.

Unemployment

Trump's claim is also false even when evaluating the unemployment rate.    In February 2020, a month before the COVID pandemic affected the economy, the unemployment rate stood at 3.5% — which was the lowest since December 1969 — but not the lowest ever. When Trump's term ended, the unemployment rate was 6.3%.

In 1953, the unemployment rate fell as low as 2.5%. Under Mr. Biden, the unemployment rate is 4%, according to the  most recent data  from May 2024. 

In January 2023 and again in April 2023, the unemployment rate was 3.4%, lower than the best month during Trump's term.

Stock market performance

On Jan. 19, 2021, the  S&P 500-stock average  closed at 67.8% above where it had been the day before Trump was inaugurated in 2017. 

According to  Investopedia ,  at the end of President Barack Obama's first term in office, the S&P closed 84.5% higher. Additionally the S&P gained 79% during President Bill Clinton's first term, and 70% during President Dwight Eisenhower's first term. So far, under President Biden, the  S&P 500 has increased almost 40% , according to calculations on June 13. 

By Laura Doan and Hunter Woodall 

Biden claims he's the only president this century that doesn't have troops dying anywhere in the world: False

Biden: "I'm the only president this century that doesn't have any — this decade — that doesn't have any troops dying anywhere in the world." 

Details : At least 16 U.S. service members have died while serving overseas during Mr. Biden's presidency. Thirteen U.S. service members  died  in an attack at the Kabul airport in Afghanistan in August 2021. Three soldiers were  killed  in an attack in Jordan in January of this year.

By Layla Ferris

Trump claims he did not refer to U.S. soldiers who were killed as "suckers and losers": False

Trump: "First of all, that was a made-up quote. 'Suckers and losers,' they made it up."

Details : Current and former U.S. military service members have detailed to CBS News multiple instances when Trump made disparaging remarks about members of the U.S. military who were captured or killed, including referring to the American war dead at the Aisle-Marne American Cemetery in France in 2018 as "losers" and "suckers."  

A senior Defense Department official and a former U.S. Marine Corps officer with direct knowledge of what was said detailed how Trump said he did not want to visit the cemetery because it was "filled with losers." These accounts were backed independently by two other officials — a former senior U.S. Army officer and a separate, former senior U.S. Marine Corps officer.   

In another conversation on the trip, Trump referred to the 1,800 Marines who died in the World War I battle of Belleau Wood as "suckers" for getting killed.  The Atlantic was first to report Trump's comments in 2020. His former chief of staff John Kelly later confirmed to CNN the essence of what Trump had said.

By James LaPorta and Sierra Sanders 

Biden claims 40% fewer people are crossing border illegally, better than when Trump was in office: Partially true         

Biden: "I've changed it in a way that now you're in a situation where there 40% fewer people coming across the border illegally; it's better than when he left office."

Details : Since Mr. Biden issued a  proclamation  banning most migrants from asylum at the U.S.-Mexico border in early June, illegal crossings there have dropped. In the past week, daily illegal border crossings have averaged roughly 2,000, according to internal Department of Homeland Security data obtained by CBS News. That's a 47% drop from the 3,800  daily average  in May.

During the height of a spike in migration faced by the Trump administration in 2019, Border Patrol recorded an average of 4,300 daily illegal crossings,  government data  show. But there were months during the  Covid-19 pandemic  when the Trump administration averaged fewer than 2,000 illegal border crossings.

By Camilo Montoya-Galvez

Trump claims migrants coming to U.S. and "killing our citizens at a level...we've never seen before": Misleading

Trump: "People are coming in and killing our citizens at a level like we've never seen before." 

Details :  Some migrants who are believed to have entered the U.S. along the southern border in recent years have been charged with murder and other heinous crimes in different parts of the country. They include the suspect in the high-profile murder of Georgia nursing student Laken Riley .

But while the data on this question is not comprehensive, available  studies  have found that migrants living in the country illegally do not commit crimes at a higher rate than native-born Americans. 

Government  statistics  also show a very small fraction of migrants processed by Border Patrol have criminal records in the U.S. or other countries that share information with American officials.

On COVID, Trump claims more people died under Biden administration than his: True, but needs context  

Trump: "Remember, more people died under his administration — even though we had largely fixed it — more people died under his administration than our administration, and we were right in the middle of it, something which a lot of people don't like to talk about. But [Biden] had far more people dying in his administration."

Details : More than 460,000 people had died from COVID-19 by the end of the week that Biden was inaugurated in 2021, while more than 725,000 have died in the three years since then, according to data from the  CDC . However, research has found that the counts of COVID-19 deaths, especially in the early days of the pandemic, were likely  undercounted .

By Julia Ingram and Jui Sarwate

In discussing abortion, Trump claims former Virginia governor, a Democrat, supported killing babies: False

Trump: "If you look at the former governor of Virginia, he was willing to do this — he said  'we'll put the baby aside and we'll determine what we'll do with the baby'.. .meaning we'll kill the baby."

Details : In a 2019 radio interview then-governor of Virginia Ralph Northam, in discussing late-term abortions,  addressed a hypothetical scenario in which a fetus was severely deformed or wasn't otherwise viable. He said, "the infant would be delivered, the infant would be kept comfortable, the infant would be resuscitated if that's what the mother and the family desired." 

Northam did not say the fetus should be killed. Killing a newborn baby — or infanticide — is illegal in every state, and not a single state is trying to change that. 

By Laura Doan and Daniel Klaidman

Trump claims Biden "went after" his political opponent in New York "hush money" case to damage him: False        

Trump: "[Biden] basically went after his political opponent (Trump) because he thought it was going to damage me, but when the public found out about these cases, 'cause they understand it better than he does, he has no idea what these cases are, but when they found out about these cases, you know what they did? My poll numbers went up, way up."

Details : There is no federal jurisdiction over a state case. The Manhattan district attorney's office is a  separate entity  from the U.S. Department of Justice. The department does not supervise the work of the Manhattan D.A.'s office, does not approve its charging decisions, and it does not try the D.A.'s cases.

By Pete Villasmil

Trump claims he brought insulin prices down for seniors: Misleading

Trump: "I'm the one that got the insulin down for the seniors. I took care of the seniors."

Details :  During Trump's time as president, Medicare created a voluntary program  in 2020  between some plans and insulin manufacturers that agreed to cap out-of-pocket costs for insulin at $35 per month. Around  half of  Medicare Advantage or stand-alone prescription drug plans ended up participating by 2021. 

David Ricks, CEO of insulin drugmaker Eli Lilly, has taken credit for pioneering the idea with Trump administration officials at a congressional  hearing  and in an  interview . In the same interview with STAT, Seema Verma, former Medicare agency chief in the Trump administration, gave Ricks the credit for the cap: "He is an unsung hero. He was actually the mastermind of all of this." 

Medicare  ended  the policy in 2023, after Mr. Biden signed into law the  Inflation Reduction Act , which capped insulin costs for Medicare beneficiaries — not just for the portion of plans participating in the program. The law capped insulin costs at the same amount of $35 per month.

By Alexander Tin and Hunter Woodall 

Trump claims Biden wants open borders: False

Trump: "He wants open borders. He wants our country to either be destroyed or he wants to pick up those people as voters." 

Details : When he took office, Mr. Biden reversed numerous Trump-era immigration policies, including a program that required migrants to await their asylum hearings in Mexico. U.S. Border Patrol has also reported record numbers of migrant apprehensions along the southern border during Mr. Biden's presidency. But Mr. Biden has never endorsed or implemented an "open borders" policy.

In fact, Mr. Biden has embraced some restrictive border policies that mirror rules enacted by his predecessor. In 2023, his administration published a regulation that disqualified migrants from asylum if they crossed into the country illegally after not seeking protection in a third country. 

Earlier this month, Mr. Biden enacted an even stricter policy: a proclamation that has partially shut down asylum processing along the border. His administration has also carried out over 4 million deportations, expulsions and returns of migrants since 2021, according to  government data .

Only U.S. citizens can vote in federal elections. Most who cross into the U.S. illegally are not on a path to permanent legal status, let alone citizenship. Even those who apply and win asylum — a process that typically takes years to complete — have to wait five years as permanent U.S. residents before applying for American citizenship. There's no evidence to suggest that the Biden administration's border policy is based on a desire to convert migrants into voters.

Biden claims Trump wants to get rid of Social Security: False        

Biden "[Trump] wants to get rid of Social Security. He thinks there's plenty to cut in social security. He's wanted to cut Social Security and Medicare, both times."

Details : Trump has repeatedly  said  he will try to protect Medicare and Social Security. Trump said in a March 21 Truth Social  post  that he would not "under any circumstance" allow Social Security to "be even touched" if he were president. Trump had said in a CNBC  interview  on March 11 that "there is a lot you can do" in terms of "cutting" spending under Social Security. Mr. Biden  said  the comments were proof Trump aimed to make cuts in the programs, but a Trump campaign spokesman  said  Trump was referring to "cutting waste and fraud," not Social Security entitlements.

Trump claims Biden has the "largest deficit" in history of U.S.: False

Trump: "But he's (Biden) got the largest deficit in the history of our country."

Details : The national deficit was the largest it had been in over two decades under Trump's administration, not Mr. Biden's, according to  data from the U.S. Treasury . The deficit peaked in fiscal year 2020 at $3.13 trillion, and declined to $1.7 trillion by the end of fiscal year 2023.

By Julia Ingram

• Presidential Debate
• Donald Trump

Arden Farhi is the senior White House producer at CBS News. He has covered several presidential campaigns and the Obama, Trump and Biden administrations. He also produces "The Takeout with Major Garrett."

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Fact-checking Biden and Trump's claims at the first debate

Forget alternative facts and political spin: Thursday's presidential debate was more like a tsunami of falsity.

Former President Donald Trump unleashed a torrent of misinformation on topics from terrorism to taxes during the first debate of the 2024 general election, while President Joe Biden flubbed figures and facts about military deaths and insulin prices.

More than a dozen NBC News reporters, editors and correspondents fact-checked the key claims the presidential candidates made Thursday night. Here they are by topic:

Economy, trade and health care

Fact check: did biden inherit 9% inflation.

“He also said he inherited 9% inflation. Now, he inherited almost no inflation, and it stayed that way for 14 months, and then it blew up under his leadership,” Trump said about Biden.

This is false.

The inflation rate when Biden took office in January 2021 wasn’t 9%. It was 1.4%. It has risen on his watch, peaking at about 9.1% in June 2022, but by last month it had come down to 3.3%. Pandemic-related stimulus policies put in place by both Trump and Biden were blamed, in part, for the rise in the inflation rate.

Fact check: Did Biden lower the cost of insulin to $15 a shot?

“We brought down the price of prescription drugs, which is a major issue for many people, to $15 for an insulin shot — as opposed to $400,” Biden said.

Biden capped the cost of insulin at $35 a month under Medicare, not $15 a shot, and some drug companies have matched that cap. The price cap doesn’t apply to everyone , however. 

What’s more, Biden’s also significantly overstating how much insulin cost before the change. A 2022 report by the Department of Health and Human Services found that patients using insulin spent an average of $434 annually on insulin in 2019 — not $400 a shot.

Fact check: Did Trump lower the cost of insulin?

Trump claimed credit for lowering the cost of insulin for seniors, saying, “I am the one who got the insulin down for the seniors.”

That is mostly false.

In 2020, Trump created a voluntary program under Medicare Part D. The program allowed Medicare Part D plans to offer some insulin products for no more than $35 per month. It was active from 2021 to 2023, with fewer than half of the plans participating each year. 

In 2022, Biden signed the Inflation Reduction Act, which included a provision that lowered the out-of-pocket cost for people on Medicare to $35 a month and covered all insulin products. The cap didn’t apply to those with private insurance. However, after the law was implemented, insulin manufacturers voluntarily lowered the out-of-pocket cost to $35 a month for people with private insurance.

Fact check: Does Biden want to raise ‘everybody’s taxes’ by four times?

“Nobody ever cut taxes like us. He wants to raise your taxes by four times. He wants to raise everybody’s taxes by four times,” Trump claimed. “He wants the Trump tax cuts to expire.”

Biden’s tax plan “holds harmless for 98% of households,” said Kyle Pomerleau, senior fellow at the conservative American Enterprise Institute. And Biden wants to extend the majority of the Trump tax cuts, too, though he has advocated for hiking taxes on very high earners.

Fact check: Biden said the U.S. trade deficit with China is at its lowest since 2010

“We are at the lowest trade deficit with China since 2010,” Biden said.

This is true.

The U.S. had $279 billion more in imports than exports to China last year, the lowest trade deficit with the world’s second-largest economy since 2010. The highest deficit in recent years was $418 billion, in 2018, when Trump began a trade war with China. 

The decline has been driven largely by tariffs that Trump imposed in office and that Biden has maintained and in some cases expanded.

Fact check: Are immigrants taking ‘Black jobs’?

Asked about Black voters who are disappointed with their economic progress, Trump claimed Black Americans are losing their jobs because of illegal border crossings under Biden’s administration.

“The fact is that his big kill on the Black people is the millions of people that he’s allowed to come through the border. They’re taking Black jobs now,” Trump said.

There’s no evidence that undocumented immigrants are taking jobs away from Black Americans. In fact, according  to the Bureau of Labor Statistics , the Black unemployment rate fell to 4.8% in April 2023 — an all-time low. Before that, the Black unemployment rate was as high as 10.2% in April 2021.

Immigration

Fact check: did trump end catch and release.

“We ended ‘catch and release,’” Trump said.

Trump did not end “catch and release,” a term used to describe the practice of releasing migrants into the country with court dates while they await court hearings. The U.S. doesn’t have enough facilities to detain every migrant who crosses the border until they can see judges, no matter who is president, so Trump — like Barack Obama before him and Biden after him — released many migrants back into the U.S.

Fact check: Did the Border Patrol union endorse Biden?

“By the way, the Border Patrol endorsed me, endorsed my position,” Biden said.

The National Border Patrol Council, the labor union for U.S. Border Patrol agents and staff members, has endorsed Trump. 

“The National Border Patrol Council has proudly endorsed Donald J. Trump for President of the United States,” the group’s vice president, Hector Garza, said in a statement shared exclusively with NBC News. 

The union posted on X , “to be clear, we never have and never will endorse Biden.”

Biden may have been referring to a Senate immigration bill that he backed, which earned the union’s endorsement .

Fact check: Did Trump have ‘the safest border in the history of our country’?

“We had the safest border in the history of our country,” Trump said.

It’s a clear exaggeration. In 2019, the last year before the Covid-19 pandemic brought down border crossings, there were roughly 860,000 illegal border crossings, far more than in any year during the Obama administration.

Fact check: Trump says Biden is allowing ‘millions’ of criminals to enter U.S.

“I’d love to ask him … why he’s allowed millions of people to come in from prisons, jails and mental institutions to come into our country and destroy our country,” Trump said.

There is no evidence of this.

Venezuela doesn’t share law enforcement information with U.S. authorities, making it very hard to verify criminal histories of immigrants coming to the U.S. But there’s no evidence that Venezuela is purposefully sending “millions” of people from mental institutions and prisons to the U.S.

Fact check: Did Virginia’s former governor support infanticide?

“They will take the life of a child in the eighth month, the ninth month and even after birth. After birth. If you look at the former governor of Virginia, he was willing to do so, and we’ll determine what we do with the baby. Meaning we’ll kill the baby. ... So that means he can take the life of the baby in the ninth month and even after birth. Because some states, Democrat-run, take it after birth. Again, the governor, the former Virginia governor, put the baby down so that we decide what to do with it. He’s willing to, as we say, rip the baby out of the womb in the ninth month and kill the baby. Nobody wants that to happen, Democrat or Republican; nobody wants it to happen,” Trump said.

While some Democrats support broad access to abortion regardless of gestation age, infanticide is illegal, and no Democrats advocate for it. Just 1% of abortions are performed after 21 weeks’ gestation, according to the Centers for Disease Control and Prevention .

Trump first made the claim in 2019, after Virginia’s governor at the time, Ralph Northam, made controversial remarks in discussing an abortion bill. NBC News debunked the claim then, reporting that Northam’s remarks were about resuscitating infants with severe deformities or nonviable pregnancies. 

Asked on a radio program what happens when a woman who is going into labor desires a third-trimester abortion, Northam noted that such procedures occur only in cases of severe deformities or nonviable pregnancies. He said that in those scenarios, “the infant would be resuscitated if that’s what the mother and the family desired, and then a discussion would ensue between the physicians and the mother.”

Terrorism, foreign policy and the military

Fact check: trump said there was ‘no terror’ during his tenure.

“That’s why you had no terror, at all, during my administration. This place, the whole world, is blowing up under him,” Trump said.

There were two ISIS-inspired terrorist attacks while Trump was president. The first occurred in October 2017, when Sayfullo Saipov killed eight people and injured a dozen more in a vehicle ramming attack on the West Side Highway bike path in New York City. The second occurred in December 2017, when Akayed Ullah injured four people when he set off a bomb strapped to himself.

Fact check: Biden suggests no troops died under his watch

“The truth is I’m the only president this century that doesn’t have any this decade and any troops dying anywhere in the world like he did,” Biden said.

The Defense Department confirmed that 13 U.S. service members were killed in a suicide bombing attack at Abbey Gate at the Kabul airport by a member of ISIS-K as the U.S. was leaving Afghanistan. 

Environment

Fact check: did trump have the ‘best environmental numbers ever’.

“During my four years, I had the best environmental numbers ever, and my top environmental people gave me that statistic just before I walked on the stage, actually,” Trump said.

The figure Trump is referring to is the fact that carbon emissions fell during his administration. He posted the talking points his former Environmental Protection Agency chief emailed him on social media before the debate.

And it’s true that carbon emissions are falling — they have been dropping for years. Emissions particularly plunged in 2020, dropping to levels around those in 1983 and 1984. That drop was in large part thanks to Covid lockdowns, and emissions rose again when air travel and in-person working resumed. 

Still, climate activists and experts are quick to note that those drops are nowhere near enough to head off predicted catastrophic effects of global warming. Other major countries cut their emissions at a much faster rate during the Trump administration.

Fact check: The Jan. 6 crowd was not ‘ushered in’ by the police

“If you would see my statements that I made on Twitter at the time and also my statement that I made in the Rose Garden, you would say it’s one of the strongest statements you’ve ever seen. In addition to the speech I made in front of, I believe, the largest crowd I’ve ever spoken to, and I will tell you, nobody ever talks about that. They talk about a relatively small number of people that went to the Capitol and, in many cases, were ushered in by the police. And as Nancy Pelosi said, it was her responsibility, not mine. She said that loud and clear,” Trump said.

During a lengthy answer to a question about whether he would accept the result of the 2024 election and say all political violence is unacceptable, Trump made several false statements, including the claim that police “ushered” rioters into the U.S. Capitol and that then-House Speaker Nancy Pelosi, D-Calif., said it was her responsibility to keep the chamber safe. 

Video and news reports of the Jan. 6 riots clearly captured the U.S. Capitol under attack by pro-Trump crowds who overran the law enforcement presence around and inside the complex. 

On Pelosi, Trump was most likely referring to video shot by Pelosi’s daughter Alexandra for an HBO documentary that showed her during the events of Jan. 6, 2021, tensely wondering how the Capitol was allowed to be stormed.

“We have responsibility, Terri,” Pelosi tells her chief of staff, Terri McCullough, as they leave the Capitol in a vehicle. “We did not have any accountability for what was going on there, and we should have. This is ridiculous.”

“You’re going to ask me in the middle of the thing, when they’ve already breached the inaugural stuff, ‘Should we call the Capitol Police?’ I mean the National Guard. Why weren’t the National Guard there to begin with?” Pelosi says in the video. 

“They clearly didn’t know, and I take responsibility for not having them just prepare for more,” she says. 

Many allies of Trump have tried for the more than three years since the riots to paint Pelosi as somehow being responsible for the violence. Some Trump-backing Republicans have, for example, falsely claimed that she blocked the National Guard from going to the Capitol during the riots.

And everything else ...

Fact check: trump skipped world war i cemetery visit because the soldiers who died were ‘losers’.

Biden said that Trump “refused to go to” a World War I cemetery and that “he was standing with his four-star general” who said Trump said, “I don’t want to go in there, because they’re a bunch of losers and suckers.”

In 2018, during a trip to France, Trump canceled a visit to an American cemetery near Paris, blaming weather for the decision. 

But in September 2020, The Atlantic reported that Trump had axed the visit because he felt that those who’d lost their lives and been buried there were “losers.” The magazine cited “four people with firsthand knowledge of those discussions.”

According to The Atlantic, Trump said: “Why should I go to that cemetery? It’s filled with losers.” In another conversation, The Atlantic reported, Trump said the 1,800 American Marines who died were “suckers.” 

Several media outlets confirmed the remarks, and Trump’s former White House chief of staff John Kelly also said those specific comments were true.

Fact check: Trump says Biden didn’t run for president due to 2017 Charlottesville rally

“He made up the Charlottesville story, and you’ll see it’s debunked all over the place. Every anchor has — every reasonable anchor has debunked it, and just the other day it came out where it was fully debunked. It’s a nonsense story. He knows that, and he didn’t run because of Charlottesville. He used that as an excuse to run,” Trump said about Biden.

The “Unite the Right” rally in Charlottesville, Virginia, in 2017 featured torch-bearing white supremacists marching to protest the removal of a Robert E. Lee statue and chanting racist slogans like “You will not replace us.” It turned deadly when a car plowed into a crowd .

In recent months, Trump has downplayed the violence, saying it was “nothing” compared to recent pro-Palestinian protests on university campuses.

Meanwhile, Biden has always pointed to Trump’s 2017 comments as the primary reason he decided to seek the presidency in 2020, including in his campaign announcement video back in April 2019 .

Jane C. Timm is a senior reporter for NBC News.

Julia Ainsley is the homeland security correspondent for NBC News and covers the Department of Homeland Security for the NBC News Investigative Unit.

Adam Edelman is a political reporter for NBC News.

Tom Winter is a New York-based correspondent covering crime, courts, terrorism and financial fraud on the East Coast for the NBC News Investigative Unit.

• Time & Money

Is Fayetteville your dream city? People downtown give their thoughts

People enjoying the weather in downtown Fayetteville recently shared their thoughts on the city not making a list of the top 50 places people dream of living.

According to a survey conducted by DeskUp, the top three cities worldwide that people dream of living in include Dubai, Amsterdam and New York City.

The only North Carolina city cracking the top 50 was Charlotte, which ranked 13th.

Here's what residents had to say last weekend about their dream destination and the survey results.

'I like North Carolina'

C.J. Stephenson, 17, of Linden, said her dream is to live in the Appalachian Mountains in western North Carolina, so she can stay in the state.

But she's content where she is now, she said.

"It's a lot more affordable than most places," Stephenson said. "I'd be completely happy living here the rest of my life."

'I've seen a lot of improvements'

Jon Reisher, 36, of Hope Mills, said his dream city would be Pittsburgh because of its mixture of city environment and small-town feel.

He said Fayetteville is becoming his dream city.

"It's trending that way," Reisher said. "I've seen a lot of growth. Downtown is fantastic. When I first moved here, there was basically nothing down here."

'I love being in this general vicinity'

David Dunbar, 26, of Fort Liberty, said that he most wants to live in New York City to be closer to his family.

He said he has come to enjoy living in Fayetteville.

"Fayetteville's really nice," Dunbar said. "I wish it had a couple more activities in the city that I knew about."

'I enjoy the peace and quiet'

Larry Maxwell, 64, who was shopping downtown with his granddaughter Makayla, 10, said he lives in his dream area already — his hometown of Autryville.

"I lived in the Fayetteville city limits before and I didn't like it," Maxwell said. "I'd rather be out in the rural part of the county."

'I love nature'

Samantha Spillman, 23, of Fayetteville said her dream area to live in would be Oregon because of its natural beauty.

Still, she's found some outdoor adventures here.

"I really like being out here, it's just so different," Spillman said. "Good places to hike."

Public safety reporter Joseph Pierre can be reached at [email protected] .

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4 takeaways from the first presidential debate

Domenico Montanaro

President Biden and former President Donald Trump participate in the first presidential debate of the 2024 elections at CNN's studios in Atlanta on June 27. Andrew Caballero-Reynolds/AFP via Getty Images hide caption

If some people who listened to the radio in 1960 thought Richard Nixon won the presidential debate with John F. Kennedy, then maybe people reading the transcript of Thursday night’s match-up would think President Biden won.

But elections aren’t won in transcripts. The reality is, fairly or not, debates are often about optics — how the candidates present themselves, defend their records and parry attacks.

Fact check: What did Biden and Trump claim about immigration in the debate?

And that’s why so many Democrats are ringing the fire alarms after the first general-election presidential debate of 2024. The Biden campaign said the president had a cold to explain why he sounded so hoarse and weak. But Biden’s stumbles right from the beginning played into his biggest vulnerability — his age and whether the 81-year-old is up to the challenge of handling four more years in office.

There were issues for Trump, too, as he continued to spread falsehoods and bathe in the kinds of conspiratorial grievances that have turned off many voters.

Not much has changed the dynamics of this race; will anything that happened Thursday night make a difference either?

Here are four takeaways from the first Biden-Trump debate of this campaign:

1. First and foremost, let’s talk about the elephant in the room – Democrats have to be wondering if they’d be better off with someone else as their nominee.

Neither candidate is the official nominee yet. The national political conventions haven’t happened — but it’s next to impossible that Democrats would replace Biden.

Still, given he delivered the kind of performance Democrats feared, party leaders, strategists and many voters, frankly, had to be wondering during this debate what it would be like if any of a handful of other Democrats were standing on that stage.

Biden got a bit stronger as the debate went on, especially on foreign policy. He had some one-liners, like calling Trump a “whiner” when Trump wouldn’t definitively say that he would accept the results of the 2024 election. But Biden often wasn’t able to show vigor or consistently convey what he wanted to say. He simply couldn’t deliver the kinds of happy-warrior blows with that toothy smile audiences have seen from Biden in years past.

“Sometimes the spin don’t spin,” one Democratic strategist texted midway through the debate when asked for reaction.

2. If how Biden sounded wasn’t bad enough, the visuals might have been equally as bad.

An important rule of thumb for candidates — and moderators — in debates is to be conscious of how things look, of how you look, of what people are seeing at home. And what people saw — and this was predictable — was a split screen.

What to know about the key policies that got airtime in the presidential debate

Biden wasn’t able to use that to his advantage at all, even as Trump doled out falsehood after falsehood. Instead, he looked genuinely shocked and confused, which is never a good look.

Trump and his base might not care about late-night comedy, but this week’s monologues are going to sting Democratic voters.

3. The format — and hands-off moderators — benefited Trump.

The muting of the candidates was likely intended to make the debate calmer and not allow Trump to run roughshod over the moderators or his opponent. But it had the effect of making Trump seem more sedate than usual.

Trump employed rounds of verbal jujitsu, in which he threw back his own vulnerabilities and directed them toward Biden. He was even able at one point, during a strange exchange about golf handicaps, to say, “Let’s not act like children.”

The moderation, or lack thereof, also allowed Trump to spread falsehoods and hyperbole without being interrupted or corrected. CNN indicated before the debate that the moderators were not going to play a strong role in fact checking the candidates, and they lived up to that.

They left it to the candidates, essentially, and with Biden unable to deliver in real time and the moderators declining to, the audience was left with a salad bowl full of rotten eggs and moldy lettuce that passed for facts.

4. This debate might not move the needle much, if at all.

Despite Biden’s struggles, which will understandably get the headlines, Trump had some difficult moments, too, especially in the second half of the debate.

In addition to spreading myriad falsehoods, he did little to credibly defend his conduct on and before the Jan. 6 siege on the Capitol; he used the kind of hyperbolic and vituperative language that has long turned off swing voters; and showed why many are concerned about some of his positions on the issues, especially on abortion and how the U.S. should be represented on the world stage.

So despite Biden’s shortcomings, millions will still likely vote for Biden, anyway, because he’s not Trump.

The bottom line is: Americans have said they are unhappy with their choices, and, in this – the biggest moment of the 2024 presidential campaign yet — it was clear why.

Correction June 28, 2024

A previous version of this story referenced this week's live SNL episode but in fact the show is on its summer hiatus.

Six Takeaways From the First Presidential Debate

In a testy, personal clash, President Biden failed to ease worries about his age, Donald Trump forcefully made his case (with wild claims and exaggerations) and the moderators held their fact-checking fire.

The debate stage in Atlanta on Thursday night. Credit... Kenny Holston/The New York Times

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By Shane Goldmacher and Jonathan Swan

Shane Goldmacher reported from the debate in Atlanta, and Jonathan Swan from Washington.

• June 28, 2024

President Biden struggled through his first debate of the 2024 campaign against Donald J. Trump, meandering and mumbling through answers as the former president pressed his case for a second term with limited resistance from his rival.

They disagreed on abortion, inflation, climate change, foreign affairs and immigration. But the sharpest contrast was in their presentation.

Mr. Trump was confident and forceful, even as he let loose a stream of misleading attacks and falsehoods. Mr. Biden spoke with a hoarse and halting voice, closing his eyes occasionally to gather thoughts that sometimes couldn’t be corralled. Democratic anxiety rose by the minute. About halfway through, people close to Mr. Biden put out word that he had a cold.

Mr. Trump relentlessly hammered Mr. Biden on areas of vulnerability, sending exaggerations and embellishments — he was the “greatest” and his opponent the “worst” — flying unchecked through the audience-free CNN studio in Atlanta.

Here are six takeaways:

Biden stumbled over his words as he answered a question on the national debt.

“We’d be able to wipe out his debt. We’d be able to help make sure that all those things we need to do child care, elder care, making sure that we continue to strengthen our health care system, making sure that we’re able to make every single solitary person eligible for what I’ve been able to do with the — with, with the Covid, excuse me. With dealing with everything we have to do with — look, if — we finally beat Medicare.” “Thank you, President Biden. President Trump.” “He was right. He did beat Medicaid, beat it to death, and he’s destroying Medicare.”

The debate exposed Biden’s biggest weakness.

Mr. Biden’s allies desperately hoped he could turn in a commanding performance to calm voters’ persistent concerns about his age.

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