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| Analyse de variance à deux facteurs (ANOVA à deux facteurs)× | Analyse de la variance de Welch× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Hypothesis test | Hypothesis test |
| Année d'origine≠ | 1925 | 1951 |
| Auteur d'origine≠ | Ronald A. Fisher | B. L. Welch |
| Type≠ | Parametric factorial mean comparison | Parametric mean comparison (heteroscedastic) |
| Source fondatrice≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | Welch, B.L. (1951). On the Comparison of Several Mean Values. Biometrika, 38(3/4), 330–336. link ↗ |
| Alias | factorial ANOVA, two-factor ANOVA, İki Yönlü ANOVA | Welch's F-test, heteroscedastic one-way ANOVA, Welch ANOVA — Heterojen Varyans ANOVA |
| Apparentées≠ | 6 | 3 |
| 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. | Welch ANOVA is a parametric hypothesis test that compares the means of three or more independent groups when their variances are not equal. Introduced by B. L. Welch in 1951, it replaces classic one-way ANOVA whenever the homogeneity-of-variance assumption fails, while still requiring approximately normal data. |
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