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Analyze another fileNon-parametric Kruskal-Wallis test compares rank-based distributions across groups without assuming normality, followed by Dunn post-hoc pairwise comparisons with p-value adjustment for multiple testing
Use when comparing distributions across 3+ groups and normality assumptions cannot be met, or when working with ordinal data
Do not use if data is normally distributed (use one-way ANOVA instead) or if you have fewer than 3 groups (use Mann-Whitney U test)
Built for: Research scientists, biostatisticians, data analysts, quality engineers, social science researchers, clinical trial analysts
Typical data source: CSV with a categorical grouping variable (e.g., treatment group, education level, department) and one or more numeric outcome measures across 3 or more independent groups
Dataset with 4 columns
Minimum 30 rows
Non-parametric alternative to one-way ANOVA. Test whether math/reading/writing score distributions differ across parental education levels when normality assumptions fail.
Median, IQR, and sample size for each education group across all score outcomes
Box plots showing score distribution shape and median for each education group
Kruskal-Wallis H statistic, degrees of freedom, p-value, and epsilon-squared effect size for each outcome
Median scores by education group showing which group ranks highest and lowest
Heatmap of Dunn post-hoc adjusted p-values showing which group pairs differ significantly
Ranked list of significant pairwise group comparisons after Bonferroni correction
Plain-English interpretation — what the numbers mean, what's significant, and what to do next.
Need something simpler? Tf038 Live Ttest — When you only have two groups to compare -- the t-test or its nonparametric equivalent is designed for exactly two-group comparisons
Need more power? Anova Factorial — When your data meets normality assumptions and you want to test the effects of two or more factors simultaneously with interactions
Similar: Ancova Analysis, Anova Factorial
Compare academic outcomes across demographic groups
Upload student records with a grouping variable (e.g., parental education) and a numeric outcome (e.g., exam score). The Kruskal-Wallis test reveals whether the distributions differ across groups without assuming normality, and Dunn post-hoc comparisons identify which specific groups drive the differences.
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
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