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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.
Bonferroni correction: when should you use it, and what are the alternatives?
What a Bonferroni correction protects against, why it costs so much power, and how Holm and Benjamini-Hochberg compare.
Read the answer →What does r mean when it is reported next to a t test, and how do you turn it into d?
Why papers report an r with a t test, how it is computed from t, what r squared means, how to convert r to Cohen's d, and how to report it in APA style.
Read the answer →t test or Mann-Whitney in small samples: how do you choose?
Why a normality pre-check is a weak way to pick a t test or a rank test with small n, what a power simulation shows, and where permutation tests fit.
Read the answer →Need more than an answer?
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