Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test H de Kruskal-Wallis× | Test par permutation (ou randomisation)× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille≠ | Hypothesis test | Regression model |
| Année d'origine≠ | 1952 | 2005 |
| Auteur d'origine≠ | William Kruskal & W. Allen Wallis | Good (2005); Edgington & Onghena (2007); resampling tradition |
| Type≠ | Nonparametric group comparison | Nonparametric resampling test |
| Source fondatrice≠ | Kruskal, W. H. & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621. DOI ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| Alias | Kruskal-Wallis H test, one-way ANOVA on ranks, Kruskal-Wallis one-way analysis of variance, Kruskal-Wallis Testi | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| Apparentées | 5 | 5 |
| Résumé≠ | The Kruskal-Wallis H test is a nonparametric hypothesis test that compares three or more independent groups to decide whether their distributions (typically their medians) differ. Introduced by William Kruskal and W. Allen Wallis in 1952, it works on ranks rather than raw values and is the distribution-free counterpart to one-way ANOVA. | The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value. |
| ScholarGateJeu de données ↗ |
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