StatsTest Blog
Experimental design, data analysis, and statistical tooling for modern teams. No hype, just the math.
Cochran's Q Test: McNemar for Three or More Conditions
A practical guide to Cochran's Q test for comparing binary outcomes across three or more related conditions. Learn when to use it, how to interpret results, and post-hoc follow-ups.
Welch's ANOVA: When Group Variances Differ
Welch's ANOVA handles unequal variances across groups without requiring the homogeneity assumption. Learn when to use it instead of standard one-way ANOVA and how to follow up.
Comparing More Than Two Groups: A Complete Guide
How to compare means, medians, and distributions across three or more groups. Covers ANOVA, Kruskal-Wallis, post-hoc tests, and when each method is appropriate.
Controlling for Covariates: ANCOVA vs. Regression
When and how to control for covariates in group comparisons. Covers ANCOVA, regression adjustment, and the key assumptions that make covariate adjustment valid.
Heteroskedastic Groups: When Variances Differ and What to Do About It
How to handle multi-group comparisons when variances are unequal. Covers Welch's ANOVA, Games-Howell post-hoc, and why this matters more than non-normality.
Kruskal-Wallis Test: When It's Appropriate and Post-Hoc Strategy
Understanding the Kruskal-Wallis test for comparing multiple groups without normality assumptions. Covers what it actually tests, when to use it, and how to follow up with Dunn's test.
One-Way ANOVA: Assumptions, Effect Sizes, and Proper Reporting
A practical guide to one-way ANOVA covering assumptions, diagnostics, effect size measures (eta-squared, omega-squared), and how to report results properly.
Post-Hoc Tests: Tukey, Dunnett, and Games-Howell Decision Tree
How to choose the right post-hoc test after ANOVA. Covers Tukey's HSD, Dunnett's test, Games-Howell, Scheffé, and provides a clear decision tree for selection.
Testing Trends Across Ordered Groups: Jonckheere-Terpstra and Alternatives
When your groups have a natural order (dose levels, experience tiers, usage intensity), standard ANOVA ignores this structure. Learn about trend tests that leverage ordering for more power.
Two-Way ANOVA vs. Regression: Understanding Interactions for Product Teams
When to use two-way ANOVA versus regression for analyzing experiments with multiple factors. Covers interactions, main effects, and practical interpretation for product analytics.
