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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.
What should you do after rejecting the null hypothesis?
A significant result is a starting point, not a conclusion. Estimate the effect, check that it is robust, and replicate before you treat it as established.
Read the answer →Why is accuracy a poor way to judge a classification model?
Why the share of correct labels misleads with rare outcomes, ignores probabilities and costs, and which measures (Brier score, log loss, AUC) to use instead.
Read the answer →How to interpret the F statistic and p value in a one-way ANOVA
What the F ratio in an ANOVA table measures, how it maps onto the p value and the critical F, and what a significant F does and does not tell you.
Read the answer →Need more than an answer?
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