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Experimental design, data analysis, and statistical tooling for modern teams. No hype, just the math.

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All topicsA/B TestingAssumptionsBayesian MethodsCausal InferenceDifferenceDistributionsEffect SizesGoodness of FitModel EvaluationMulti-Group ComparisonsPredictionRegressionRelationshipReportingSurvival AnalysisTime SeriesTwo-Group Comparisons
Cochran's Q Test
DifferenceJan 29New

Cochran's Q Test

Cochran's Q Test compares proportions across three or more related groups. Use it when the same subjects are measured under multiple conditions and the outcome is binary (success/failure).

DifferenceProportional Variable of InterestMany Sample Tests (3+ groups)
Two-Way ANOVA
DifferenceJan 29New

Two-Way ANOVA

Two-Way ANOVA tests the effect of two independent factors (and their interaction) on a continuous outcome. Use it when you have two categorical grouping variables and want to know if either or both affect your outcome.

DifferenceContinuous Variable of InterestMany Sample Tests (3+ groups)