APA 7 Statistics Report Generator
Generate APA 7 result sentences from t, F, p, r, and common effect sizes.
This tool turns common statistical output into APA 7 style report sentences for independent and paired t tests, one-way and two-way ANOVA, chi-square tests, Pearson correlations, and simple regression. It also adds a plain-language interpretation so the statistical wording and significance decision stay aligned.
Tool area
How to use
- Choose a test type so only the relevant fields are shown.
- Enter the statistic, degrees of freedom, p value, and available effect size.
- Add variable names, group names, means, or standard deviations when useful.
- Copy the generated sentence and verify it against your formal output.
Use cases
- Format an independent-samples t test as “t(df) = value, p = .023, d = 0.89.”
- Report ANOVA results with F, degrees of freedom, p value, and eta squared.
- Check that p < .001 is never written as p = 0.000.
FAQ
- Does this replace statistics software?
- No. It formats and explains values you provide; the analysis itself should come from appropriate software or verified calculations.
- How are p values formatted?
- Values below .001 are shown as p < .001. Other values use three decimals without a leading zero, such as p = .023.
- Can it describe non-significant results?
- Yes. The wording switches based on the p value you enter.
- Are effect sizes required?
- No. Optional effect sizes are included when entered and omitted when blank.
- Can I paste the sentence directly into a paper?
- Treat it as a strong draft, then adjust for your course, journal, or advisor requirements.
Privacy & local processing
🔒 This tool runs entirely in your browser. No data is uploaded to any server.
All inputs and generated text stay in your browser and are not uploaded to FreeTools.
Trust & usage note
This tool runs mainly in your browser. Your input is not actively uploaded to a server. Avoid entering highly sensitive data. Results are for reference only.
Disclaimer
This tool helps with formatting and interpretation, but users should still confirm their statistical design and assumptions.
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