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- No jargon required. Describe your data and your goal the way you'd explain it to a colleague.
- 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
- Reviewer 2 Criticized Your Shortened Scale? How to Defend It
- How to Shorten a Survey Scale Without Losing Validity
- The Data Audit Checklist to Run First
- FIML vs. Multiple Imputation: Which to Use?
- When a Reviewer Challenges Your Model
- Power for Cluster-Randomized Trials Isn't Simple
- How Much Does a Statistical Consultant Cost?
Answers
Recent questions, answered
Plain-language answers to statistics questions people are asking.
Does k-means make assumptions? Its drawbacks explained
Why k-means, though 'just an optimization', behaves as if clusters were round, equally spread and equally sized, and what happens when they are not.
Read the answer →Why does a t test use the t distribution and ANOVA the F distribution?
How the t, F and chi-square reference distributions are derived from the way each test statistic is built, and what to do when no formula exists.
Read the answer →Where should histogram bin edges go when your data are rounded?
When values are recorded to a fixed unit, put histogram bin edges halfway between the possible values. Here is why, and how counts differ.
Read the answer →Need more than an answer?
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