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- Rather work it out yourself? Try the test chooser below.
Interactive guide
Which statistical test should I use?
Answer a few plain-language questions. You'll get a suggested test, what to check before you trust it, and links to free tools.
A starting point, not a substitute for looking at your data. Design details such as clustering, missing data, and multiple comparisons can change the right answer.
Free resources
Free tools and guides
These live on the DASS site and are free to use.
Tools
Power analysis calculators
Plan sample size for t-tests, ANOVA, correlations, chi-square, and multilevel designs.
Open calculators →APA 7 results formatters
Turn statistical output into clean, copy-ready APA sentences. Runs in your browser.
Open formatters →Check a reported p-value
Recompute the exact p from a t, F, chi-square, or correlation statistic and compare it to what was reported.
Check a p-value →Guides
Answers
Recent questions, answered
Plain-language answers to statistics questions people are asking.
How do you compare medians when the groups differ in shape and spread?
Why Mann-Whitney is not a test of medians when shapes differ, and how Mood's median test and a bootstrap interval compare medians directly.
Read the answer →Kolmogorov-Smirnov, t test or Mann-Whitney: which detects a change from a baseline?
What each two-sample test detects, why Kolmogorov-Smirnov misses changes in spread with small samples, and how to compare against a baseline.
Read the answer →How do you interpret the ICC when random effects are nested?
With readings nested in stations nested in sites, one model gives several ICCs. Which one answers which question, with R and Python examples.
Read the answer →Need more than an answer?
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