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Turn a t test, ANOVA, correlation, regression, chi-square, descriptives, reliability, or nonparametric result into a clean, copy-ready APA 7 sentence — plus a standalone check for a reported p-value, the same class of check as the statcheck R package. Every formatter recomputes what it can and preserves italics when pasted into Word or Google Docs.
Open the formatters →Solve for the sample size a study needs, or the power a planned sample already has — for t tests, one-way ANOVA, correlation, and chi-square, plus a multilevel/cluster-randomized-trial MDES calculator with sensitivity charts and a proposal-ready methods paragraph.
Open the calculators →Compare two AI models scored on the same eval items: the accuracy gap with a confidence interval and a paired McNemar test, plus Python and R code that reproduces the result. Enter counts or paste per-item results; checked against R and SciPy.
Compare two models →A standalone power and sample-size planner for two means, one-sample or paired means, correlation, and two proportions, with a live power curve and a copyable reporting sentence. Its t-test results match R exactly.
Visit statpower.org ↗ FreeStuck on a statistics question? Send it to the DASS team, or use the free test chooser to find the right analysis for your data.
Visit askstats.net ↗A reporting-completeness checker is next — a quick scan for the kind of thing that usually means digging up an old textbook or bugging a colleague.
Statistical and methods QA for manuscripts, dissertations, and grant proposals — a free 30-minute consult to talk through what the tool found.
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