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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.
Significant ANOVA but no significant pairwise comparisons: how can that happen?
Why a one-way ANOVA F test can reject while every pairwise or Tukey comparison does not (and the reverse), and how far apart their p values can get.
Read the answer →Factor analysis vs PCA: what is the difference?
PCA compresses all the variance in your variables into components; factor analysis models only the shared variance as coming from hidden factors.
Read the answer →Why can a CI for Cohen's d include zero when the t test is significant?
Why an effect size interval for Cohen's d can cross zero while the mean difference interval does not, and which d and interval agree with the test.
Read the answer →Need more than an answer?
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