The results chapter has one job: report what the data showed, clearly and without bias. Mixing in interpretation, speculation, or comparison to prior literature too early is the most common structural mistake, that work belongs in your discussion chapter.
| Results Chapter | Discussion Chapter |
|---|---|
| "The regression model explained 34% of variance (R² = .34, p < .001)" | "This level of explained variance suggests other unmeasured factors may play a substantial role, consistent with Smith's (2020) argument that..." |
| Reports the finding | Interprets what the finding means |
| No comparison to prior literature | Connects findings back to the literature review |
| Organized by research question | Organized by implication or theme |
A quick self-check: if a sentence in your results chapter starts with "this suggests," "this indicates," or references a citation explaining the finding, it likely belongs in discussion instead. Results chapters report; discussion chapters explain.
Because "results" and "findings" are sometimes used loosely and interchangeably, it's worth being precise here: this guide focuses on the quantitative results chapter. The one built around descriptive statistics, inferential tests, tables of output, and figures like bar charts, scatterplots, or box plots. If your dissertation is qualitative and your data is themes, categories, and participant quotes rather than numbers, the reporting conventions are different enough that they deserve their own treatment. See our Results/Findings Chapter guide for how a qualitative "findings" chapter is organized and why the framing genuinely differs from a quantitative results chapter, not just in vocabulary but in structure and voice.
Before any inferential test appears, a quantitative results chapter should ground the reader in who and what was actually measured. That means reporting sample size, response rate, and basic demographic or sample characteristics (means and standard deviations for continuous variables, frequencies and percentages for categorical ones) before moving into hypothesis testing. Skipping straight to a regression table without first establishing what the sample looked like leaves the reader unable to judge whether the later inferential results are even plausible for a sample of that size and composition. A short demographic table, typically the very first table in the chapter, does this work efficiently and is expected in nearly every quantitative dissertation regardless of discipline.
Once the descriptive picture is established, each research question or hypothesis gets its own inferential result, reported in a consistent format: the test used, the test statistic, degrees of freedom where applicable, the p-value, and, critically, and often missed by students, an effect size (Cohen's d, eta-squared, R², odds ratio, or the equivalent for the test used). A p-value alone tells a reader whether an effect is statistically detectable; it says nothing about whether the effect is large enough to matter practically. Reporting "t(212) = 2.87, p = .004, d = 0.41" gives a committee both pieces of information in one line, and is the standard modern reporting convention that separates a rigorous results chapter from one that only clears the p < .05 bar. Confidence intervals around key estimates are increasingly expected alongside point estimates for the same reason. They show the plausible range of the true effect, not just whether zero is excluded from it.
Tables are for precision, when a reader might need the exact number, a table is the right format. Figures are for pattern, when the point is a trend, a comparison of magnitude, or a relationship between variables, a figure communicates it faster than a table of the same numbers would. A common mistake is presenting the same data as both a table and a figure with no added information in either. Pick the format that serves the specific point being made and let the other go. Every table and figure needs a number, a clear title that states what it shows without requiring the reader to consult the surrounding text, and an in-text reference that guides the reader to it at the right moment rather than leaving them to stumble across it three pages later.
Suppose a dissertation compares post-test scores between an intervention group and a control group. A weak version of this result might read: "The intervention group did better than the control group." A results-chapter-appropriate version reads instead: "Participants in the intervention group (M = 78.4, SD = 6.2, n = 61) scored significantly higher on the post-test than participants in the control group (M = 71.9, SD = 7.1, n = 58), t(117) = 5.12, p < .001, d = 0.95, indicating a large effect size." Notice what the second version does: it reports both group means and standard deviations, states the test and its result precisely, includes an effect size, and stops there. It does not speculate about why the intervention worked, does not connect the result to prior studies, and does not discuss what it means for practice. That interpretive work is exactly what the accompanying discussion chapter is for.
A master's thesis results chapter is often judged mainly on whether the numbers are correct and clearly presented. A doctoral results chapter is judged additionally on whether the reporting meets current disciplinary conventions. APA 7th edition statistical reporting standards, effect sizes and confidence intervals as a default rather than an extra, and assumption-check reporting integrated into the narrative rather than relegated to an appendix no one reads. Doctoral committees, particularly at the dissertation defense, are also more likely to probe the boundary between results and discussion directly. Asking a candidate to explain, in the room, why a particular sentence belongs in one chapter and not the other. Being able to answer that question confidently is itself part of what a defense is testing, which is one more reason the results/discussion boundary deserves more than casual attention.
Yes, typically. Quotes serve as the evidence supporting each theme. We select quotes that clearly illustrate the theme without overloading the chapter, and report them alongside frequency or prevalence where relevant. See our Results/Findings Chapter guide for the qualitative-specific version of this chapter.
As many as needed to present the findings clearly, and no more. A results chapter padded with redundant tables showing the same data multiple ways reads as filler rather than rigor.
Yes, this is common. Send your output (SPSS, R, NVivo, or coded transcripts) and we structure the narrative around your research questions.
Yes, by default. Effect sizes are close to a universal expectation in current quantitative reporting standards (APA 7th edition explicitly requires them), and their absence is one of the more common revision requests we see from committees.
That's normal and doesn't need to be evened out artificially. A question answered by a single clean statistical test may need only a short paragraph and a table, while a question involving multiple subscales may need considerably more space. Length should follow the data, not a rule about symmetry between sections.
Generally no. Raw output belongs in an appendix, if anywhere, while the chapter itself presents clean, formatted tables built from that output. Committees want to read a narrative supported by tables, not scroll through pasted software console text mixed into the prose.
Findings organized by research question, reported without premature interpretation.