Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse de variance à deux facteurs (ANOVA à deux facteurs)× | Test H de Kruskal-Wallis× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Hypothesis test | Hypothesis test |
| Année d'origine≠ | 1925 | 1952 |
| Auteur d'origine≠ | Ronald A. Fisher | William Kruskal & W. Allen Wallis |
| Type≠ | Parametric factorial mean comparison | Nonparametric group comparison |
| Source fondatrice≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | 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 ↗ |
| Alias≠ | factorial ANOVA, two-factor ANOVA, İki Yönlü ANOVA | Kruskal-Wallis H test, one-way ANOVA on ranks, Kruskal-Wallis one-way analysis of variance, Kruskal-Wallis Testi |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | Two-Way ANOVA is a parametric hypothesis test that simultaneously examines the main effects of two independent categorical factors and their interaction effect on a single continuous dependent variable. The technique was developed within the broader framework of the analysis of variance established by Ronald A. Fisher in 1925 and remains the standard approach whenever an experiment or survey includes exactly two between-subjects factors. | 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. |
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