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Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse de régression multiple× | Analyse de la variance (ANOVA)× | |
|---|---|---|
| Domaine | Statistiques de recherche | Statistiques de recherche |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1801 | 1925 |
| Auteur d'origine≠ | Carl Friedrich Gauss | Ronald A. Fisher |
| Type | Method | Method |
| Source fondatrice≠ | Draper, N. R., & Smith, H. (1966). Applied Regression Analysis. John Wiley & Sons. link ↗ | Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver and Boyd. link ↗ |
| Alias≠ | MLR, multivariate regression, linear regression | ANOVA, F-test |
| Apparentées | 4 | 4 |
| Résumé≠ | Multiple regression analysis is a statistical method for modeling the relationship between a continuous dependent variable and two or more independent variables (predictors). Originating from Gauss's early 19th-century work and formalized by Draper and Smith (1966), it estimates linear equations predicting outcomes from multiple predictors while accounting for confounding relationships, making it indispensable in epidemiology, economics, psychology, and clinical research. | ANOVA is a parametric statistical method developed by Ronald A. Fisher in 1925 that tests whether means differ significantly across three or more independent groups. By partitioning total variance into between-group and within-group components, ANOVA determines whether observed differences are likely due to treatment effects or random variation, making it fundamental to comparative research across medicine, psychology, agriculture, and engineering. |
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