Writing the Results Chapter

The results chapter is the empirical core of your dissertation, where you present your data and evidence to answer your research questions. It is a report of what you found, not a discussion of what it means. A well-crafted results chapter demonstrates scholarly rigor, builds a transparent chain of evidence, and sets the stage for the analytical discussion to follow. Your goal is to present your findings with such clarity and organization that your reader can easily understand and evaluate your work.

Organizing Your Chapter Around Research Questions or Hypotheses

The most logical and reader-friendly way to structure your results chapter is to follow the sequence of your research questions or hypotheses. This creates a direct narrative link between what you set out to investigate and what you discovered. Begin the chapter with a brief introductory paragraph that restates your study's purpose and provides a roadmap, telling the reader you will present findings for each research question in turn.

For each research question or hypothesis, create a dedicated subsection. Start the subsection by explicitly stating the question you are addressing. Then, guide the reader through the relevant analyses, presenting data in a logical flow—often moving from the general to the specific. For example, you might first present descriptive statistics to characterize your sample, then report on tests of statistical assumptions, and finally present the outcomes of your primary inferential tests. This organization transforms raw data into a coherent story of discovery.

Presenting Quantitative Results

Quantitative findings must be reported with precision and completeness. Begin with descriptive statistics, such as means, standard deviations, frequencies, and percentages, which summarize the basic features of your data. This gives the reader a clear picture of your sample. Next, for parametric tests (e.g., t-tests, ANOVA, regression), you must document your assumption checks. Briefly report your tests for normality, homogeneity of variance, linearity, or multicollinearity, as applicable, and state whether the assumptions were met.

The heart of quantitative reporting is your inferential analyses. For each statistical test, you must provide the key values that allow for evaluation and replication: the test statistic (e.g., $t$, $F$, ${\chi }^2$), degrees of freedom, p-value, and, crucially, the effect size (e.g., Cohen's $d$, ${\eta }^2$, $R^2$). While the p-value indicates whether an effect exists, the effect size tells you how large and practically meaningful it is. Always refer to tables and figures in your text (e.g., "As shown in Table 1...") and use them to complement, not duplicate, your narrative. In the text, highlight the most important patterns and numbers; let the table hold the full dataset.

Presenting Qualitative Results

Qualitative results are presented thematically, showcasing the patterns, categories, and narratives that emerged from your data analysis. Instead of reporting statistics, you are building an evidence-based argument for each theme. Start by naming and defining your central themes or categories. Provide a concise explanation of what each theme encompasses and why it is significant to your research question.

The evidence for each theme comes from your data. Integrate supporting quotes, observations, or document excerpts directly into your narrative. Choose quotes that are vivid, representative, and illustrative of the point you are making. After presenting a quote, you must engage in a minimal level of interpretation to explain how that piece of evidence connects to and supports the theme. This process of theme-definition, evidence-presentation, and brief linking commentary creates a compelling and trustworthy account of your findings. Remember, deep analysis and connection to the literature belong in the discussion chapter; here, you are showing the reader the thematic landscape you discovered.

Using Tables, Figures, and Visuals Effectively

Visual elements are powerful tools for conveying complex results efficiently. A well-designed table can present a large amount of detailed numerical data in an accessible format, while a figure (e.g., graph, chart, model, or photograph) can instantly communicate a trend, relationship, or visual pattern. Every table and figure must be numbered consecutively, have a clear and descriptive title, and be interpretable on its own, with all necessary labels and legends.

The key principle is that visuals should supplement the text, not substitute for it. In your narrative, direct the reader's attention to the visual ("Figure 2 illustrates the positive correlation between...") and then articulate the key takeaway. Avoid the pitfall of including a graph that simply repeats what you said in a sentence. Instead, use visuals to display data patterns that are cumbersome to describe verbally or to provide a reference point for detailed statistical output. Ensure all visuals adhere to your institution's formatting guidelines and scholarly conventions for your field.

What to Exclude: Maintaining a Focus on Findings

Perhaps the most critical discipline in writing the results chapter is knowing what to leave out. This chapter is for reporting findings, not interpreting them. Therefore, you must actively restrain interpretation. Do not speculate on why a result turned out a certain way, compare your findings to prior studies, or discuss the broader implications of your data. Save that crucial work for the discussion chapter.

Similarly, avoid recounting methodological steps already described in your methods chapter. You may need to briefly remind the reader of a specific test or analysis procedure for clarity, but do not re-describe your survey instrument, interview protocol, or sampling method. Finally, do not present raw data. Your chapter should consist of processed, analyzed, and synthesized results. Appendices are the appropriate place for lengthy transcripts, full survey responses, or massive raw data output.

Common Pitfalls

Data Dumping and Poor Organization: Presenting results in a disorganized stream of statistical output or lengthy, unedited quotes confuses and loses the reader. Correction: Structure every subsection around a single research question. Use subheadings, transitions, and a logical flow from descriptive to inferential, or from theme to supporting evidence, to create a clear narrative path.

Over-Interpreting or Speculating: A common mistake is to begin analyzing the "why" behind a finding in the results chapter. Statements like "This surprising result likely occurred because..." belong in the discussion. Correction: Strictly limit your writing to reporting what you found. Describe patterns, report statistics, and present themes and quotes. Let the data speak for itself here.

Inadequate or Ineffective Visuals: Using a table for two numbers, creating a cluttered and unreadable graph, or failing to reference a figure in the text undermines its utility. Correction: Only use a visual if it adds genuine clarity or efficiency. Design it for readability, ensure it is correctly labeled, and always discuss its main message in your narrative.

Weak Qualitative Evidence: Presenting themes without sufficient or compelling data excerpts, or using quotes that are trivial and not illustrative, weakens the credibility of your analysis. Correction: Select quotes that are rich, relevant, and representative. Frame each quote with a sentence introducing it and a sentence after it explaining its significance to the theme.

Summary

• The results chapter is a factual report of your findings, organized systematically by your research questions or hypotheses to provide a clear narrative.
• For quantitative studies, report descriptive statistics, checks of statistical assumptions, and inferential test results—always including effect sizes to convey practical significance.
• For qualitative studies, present identified themes with clear definitions and support each theme with carefully selected, relevant data excerpts like quotes, followed by minimal explanatory commentary.
• Use tables and figures to present complex data efficiently, ensuring they are well-designed, properly titled, and referenced in the text.
• Maintain a disciplined focus on reporting what you found; rigorously avoid interpreting, speculating on, or discussing the implications of your results in this chapter.