How to Report Statistical Results

A results section that lists numbers without a consistent format or brief interpretation leaves the reader to do the difficult work of genuinely understanding what the statistics actually show and mean. This guide covers how to report statistical results clearly, following APA statistics reporting conventions where relevant, with practical guidance for writing up results section content that actually communicates rather than just lists.

What to include for each result

• The specific statistical test actually used
• The relevant statistic and its value (e.g. t, F, r, or a regression coefficient)
• Degrees of freedom, wherever genuinely and specifically applicable
• The p-value
• An effect size, wherever your specific discipline or unit expects one

How to report statistical results: the core elements

Learning how to report statistical results well means consistently including every essential element for each test — the specific test used, the relevant statistic and its value, degrees of freedom where applicable, the p-value, and an effect size where your discipline expects one. Omitting any of these specific elements leaves a reader genuinely unable to fully evaluate your finding, even if the underlying analysis itself was actually conducted correctly.

APA statistics reporting: formatting conventions

APA statistics reporting follows specific formatting conventions worth learning precisely — italicised statistical symbols (t, F, p), specific rules around leading zeros (p = .032, not p = 0.032), and a standard order for presenting the test statistic, degrees of freedom, and p-value together in a single consistent format. Following APA statistics reporting conventions precisely, rather than approximately, signals genuine familiarity with the expected academic standard in fields where this style applies.

Keeping the format consistent

Report results in a consistent format throughout the section, following your required referencing style's conventions (such as APA) for how statistics are presented — consistency helps a reader compare results across the section. This consistency is one of the most basic expectations behind how to report statistical results professionally, and inconsistent formatting within a single results section signals carelessness even when the underlying analysis is sound.

Text, tables, and figures together

Use a table or figure to present full results clearly, and use the text to highlight and briefly interpret the specific findings most relevant to your research question — avoid simply repeating every number from a table in prose form. Writing up results section content well means striking this balance between comprehensive tabular presentation and focused, interpretive prose discussing what actually matters for your research question.

Common mistakes

• Reporting p-values without effect sizes where the discipline expects them
• Inconsistent formatting of statistics across the section
• Repeating every table value in the text instead of highlighting what matters
• Presenting results without any interpretation of their relevance to the research question
• Applying APA statistics reporting conventions inconsistently within the same results section

Writing up results section content: connecting to the research question

A genuinely strong results section, beyond correctly formatted statistics, explicitly connects each significant finding back to the original research question or hypothesis it addresses. Writing up results section content this way — not just "the result was significant" but "this supports/contradicts the hypothesis that..." — gives the statistics genuine narrative purpose rather than presenting them as a disconnected list of numbers for the reader to interpret unassisted.

How to report statistical results: non-significant findings

Learning how to report statistical results also means reporting non-significant findings with the same care and completeness as significant ones — a non-significant result is still a legitimate finding worth reporting fully, including its test statistic, degrees of freedom, and p-value, not simply noted as "not significant" without the full supporting detail a reader would need to evaluate it.

APA statistics reporting for different test types

APA statistics reporting conventions differ slightly by test type — a t-test reports degrees of freedom in parentheses immediately after the statistic, while an ANOVA reports both between-group and within-group degrees of freedom, and a correlation reports the sample size. Checking the specific APA statistics reporting convention for each test type you're using, rather than applying one format uniformly across every kind of statistic, avoids a common formatting inconsistency.

How to report statistical results for multiple comparisons

When a study involves multiple statistical comparisons, how to report statistical results correctly means addressing whether any correction for multiple comparisons was applied, since running many tests increases the risk of a false positive result appearing significant purely by chance. Reporting whether a correction like Bonferroni was used, and how it affected your significance threshold, is an important detail many students omit despite its relevance to how confidently a reader should interpret your findings.

APA statistics reporting: reporting descriptive statistics first

Before inferential statistics, APA statistics reporting conventions typically expect descriptive statistics — means, standard deviations, sample sizes — reported first, giving the reader necessary context before the inferential test results that build on them. Writing up results section content in this logical order, descriptive before inferential, helps a reader build understanding progressively rather than encountering test statistics without the basic distributional information needed to interpret them meaningfully.

Writing up results section content: organising by research question

For a study with multiple research questions or hypotheses, writing up results section content benefits from organising the section explicitly around each specific question in turn, rather than grouping all statistics together by test type regardless of which question they address. This organisation makes it considerably easier for a reader to follow which specific results address which specific research question, especially in a longer results section covering several distinct analyses.

How to report statistical results: avoiding overinterpretation

Learning how to report statistical results responsibly also means avoiding overinterpretation — a significant result supports a specific, narrow conclusion within the scope of what was actually tested, not a sweeping general claim beyond what the data and analysis can support. Keeping your interpretive language proportionate to what the statistics actually demonstrate is an important discipline that distinguishes a rigorous results section from an overreaching one.

APA statistics reporting in tables versus in-text

APA statistics reporting conventions differ slightly between in-text reporting and table presentation — a table can present full statistical detail for every variable or comparison, while in-text reporting should selectively highlight only the findings most directly relevant to your research question, referring readers to the table for complete detail rather than repeating everything in prose. Understanding this distinction is central to writing up results section content that stays readable rather than overwhelming.

A final checklist before finalising your results section

Before finalising your results section, run through a short checklist: does every reported statistic include all required elements (test, statistic value, degrees of freedom, p-value, effect size where relevant); is formatting consistent throughout following APA statistics reporting or your required style; does the text highlight key findings rather than repeating every table value; and does each significant finding connect explicitly back to your research question? This checklist confirms genuine understanding of how to report statistical results has been applied consistently throughout your specific results section.

How to report statistical results across different statistical tests

The core principles behind how to report statistical results stay consistent, but the specific elements required vary somewhat by test — a t-test needs the t-value, degrees of freedom, and p-value; an ANOVA needs the F-value, both degrees of freedom values, and p-value; a correlation needs the r-value, sample size, and p-value. Learning the specific reporting format expected for each test type you commonly use is a practical investment that pays off across many future assignments and research projects.

Writing up results section content for qualitative-quantitative mixed studies

For a study combining both qualitative and quantitative components, writing up results section content typically means presenting each component's findings using its own appropriate conventions — statistical reporting following APA statistics reporting standards for the quantitative results, and thematic discussion supported by illustrative quotes for the qualitative results — while explicitly connecting the two where they inform or support each other within the overall findings.

APA statistics reporting: common formatting errors to avoid

Common APA statistics reporting errors include using a comma instead of a period for decimals in international contexts where local convention differs, failing to italicise statistical symbols correctly, and reporting p-values as exactly zero (p = .000) rather than the more accurate "p < .001" convention APA style specifically requires. Checking your results section carefully against these specific, commonly made errors before final submission catches formatting mistakes a general proofread pass might otherwise easily miss.

How to report statistical results: sample size reporting

Explicitly stating your sample size is an essential part of how to report statistical results transparently — a reader needs this information to evaluate how much confidence a specific finding deserves, since the same effect size and p-value mean something different in a sample of twenty compared to a sample of two thousand. Reporting sample size clearly, either in the methods section, the results section, or both depending on your specific style guide, avoids leaving readers to simply guess at this crucial context.

Writing up results section content: using consistent decimal places

A subtle but noticeable inconsistency in writing up results section content is varying decimal place precision across different reported statistics without a clear rationale — reporting one mean to two decimal places and another to four, for instance. APA statistics reporting and most other style guides expect consistent precision throughout a results section, typically two decimal places for most statistics unless your specific field's convention calls for more.

How to report statistical results when using statistical software output

Statistical software often produces output with more decimal places, additional statistics, and different formatting than academic reporting conventions require, and learning how to report statistical results well means translating that raw software output into the cleaner, more selective format your specific style guide expects — not copying software output directly into your results section. This translation step is exactly where genuine understanding of what each specific statistic actually means, not just the technical ability to run software, becomes truly essential.

Bringing it together

Ultimately, learning how to report statistical results well comes down to consistency, completeness, and clear interpretation — every result formatted the same way following APA statistics reporting or your required style, every essential element included, and every finding connected explicitly back to your research question. Applying these principles consistently throughout your writing up results section content is what most reliably produces a results section that genuinely communicates, rather than one that merely lists numbers for the reader to interpret alone.

Related support

See Regression Analysis Explained for interpreting regression output specifically, or How to Present Data in an Academic Report for related presentation guidance.