Step-by-step tutorials on choosing, running, interpreting and reporting statistical tests, each linked to a free tool you can use straight away.
Answer three questions about your goal, your variables and your design, and this guide points you to the right test, with a free tool to run it.
Everything you need to compare two group means, from assumptions and Levene's test to Welch's correction, Cohen's d and an APA-ready write-up.
Compare three or more group means the right way, with a worked example covering the F-test, Welch's F, Tukey post hoc comparisons, effect sizes and APA reporting.
The nonparametric alternative to the independent t-test, explained with a worked example, effect size r and an APA-ready write-up.
Test whether two categorical variables are related, with a worked example, the expected-count rule, standardized residuals, Cramér's V and an APA write-up.
A practical guide to Cronbach's alpha, covering what the number means, acceptable values, what to do when alpha is low, and when McDonald's omega is the better choice.
Learn how to test discriminant validity with HTMT and Fornell-Larcker, which cut-offs reviewers expect, what to do when constructs overlap, and how to report it in a thesis or paper.
Why Baron and Kenny's steps are outdated, how bootstrapped indirect effects work, how to classify mediation, and how to report a simple, parallel or serial mediation model.
How to test whether an effect depends on a third variable, from building the interaction term to probing simple slopes, the Johnson-Neyman region and an APA write-up.
A line-by-line guide to multiple regression output, from R² and the F-test to unstandardized and standardized coefficients, multicollinearity checks and an APA results paragraph.