Statistical & Methods QA · DASS

Free APA 7 Results Formatters

Turn statistical output into clean, copy-ready APA 7 sentences. Every formatter runs entirely in your browser, works offline, checks the numbers you entered where an exact recomputation is possible, and preserves italics when copied into Word or Google Docs.

Check a reported p-value

Recompute the exact p from a t, F, chi-square, or correlation statistic and check it against what you reported — the statcheck idea, by hand.

Open formatter →

t-Test Formatter

Independent, paired, and one-sample designs with optional descriptives and a p-value check.

Open formatter →

ANOVA Formatter

One-way, factorial, and repeated-measures results, including effect-size notation.

Open formatter →

Correlation Formatter

Pearson and Spearman correlations with automatic degrees of freedom.

Open formatter →

Regression Formatter

A model-summary line and coefficient line in one polished result.

Open formatter →

Chi-Square Formatter

Includes the easy-to-miss sample size and Cramer's V effect size.

Open formatter →

Descriptives Formatter

Means and standard deviations, with optional sample size and range.

Open formatter →

Reliability Formatter

Cronbach's alpha and McDonald's omega with correct Greek notation.

Open formatter →

Nonparametric Formatter

Mann–Whitney U and Wilcoxon signed-rank sentences with effect size.

Open formatter →

One set of APA rules, applied everywhere

These formatters share the same APA 7 numeric and typography rules. Values bounded by 1 — such as p, r, standardized β, and effect-size coefficients — drop the leading zero. Statistics that can exceed 1 retain it. Exact p values use three decimals, while values below .001 appear as p < .001, never p = .000.

Where an exact sampling distribution is available, the tool recomputes p from the statistic and degrees of freedom and flags a mismatch worth double-checking, without assuming the entered result is wrong. Rounding, one-tailed hypotheses, and multiplicity corrections can all produce legitimate differences — the same reasoning behind the statcheck R package, which found reporting inconsistencies in roughly half of published psychology articles by running exactly this check at scale.