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- Theses, studies, program evaluations, surveys, business data.
- 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.
Interrupted time series vs event study vs difference-in-differences
All three estimate the effect of an intervention, but each builds its counterfactual differently. Here is how to tell them apart.
Read the answer →Is a normality test worth running on your data?
Normality tests answer the wrong question: with lots of data they flag harmless quirks, with little data they miss real problems. Here is what to do.
Read the answer →What does kurtosis actually tell you about your data?
Kurtosis describes how heavy a distribution's tails are, not how peaked it is. Here is how to read it, in plain language.
Read the answer →Need more than an answer?
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