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| Correction de Bonferroni× | Analyse de variance à un facteur× | |
|---|---|---|
| Domaine | Statistique | Statistique |
| Famille | Hypothesis test | Hypothesis test |
| Année d'origine≠ | 1961 | 1925 |
| Auteur d'origine≠ | Carlo Emilio Bonferroni; formalized for multiple comparisons by Olive Jean Dunn | Ronald A. Fisher |
| Type≠ | Family-wise error rate (FWER) correction | Parametric mean comparison |
| Source fondatrice≠ | Bonferroni, C. E. (1936). Teoria statistica delle classi e calcolo delle probabilità. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commerciali di Firenze, 8, 3–62. link ↗ | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ |
| Alias≠ | Bonferroni adjustment, Bonferroni method, Bonferroni procedure, FWER correction | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA |
| Apparentées≠ | 5 | 4 |
| Résumé≠ | The Bonferroni correction is a conservative, universally applicable method for controlling the family-wise error rate (FWER) when conducting multiple simultaneous hypothesis tests. Grounded in Bonferroni's 1936 probability inequality and formalized for multiple comparisons by Olive Jean Dunn in 1961, the procedure divides the target significance level α by the number of tests m, ensuring that the probability of making even one false rejection across the entire family of tests does not exceed α. | One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925. |
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