Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse de Covariance (ANCOVA)× | Analyse discriminante× | Analyse de variance à un facteur× | |
|---|---|---|---|
| Domaine | Statistique | Statistique | Statistique |
| Famille≠ | Hypothesis test | Latent structure | Hypothesis test |
| Année d'origine≠ | 1932 | 1936 | 1925 |
| Auteur d'origine | Ronald A. Fisher | Ronald A. Fisher | Ronald A. Fisher |
| Type≠ | Parametric group comparison with covariate control | Supervised classification and dimension reduction | Parametric mean comparison |
| Source fondatrice≠ | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗ | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ |
| Alias≠ | analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi) | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA |
| Apparentées | 4 | 4 | 4 |
| Résumé≠ | ANCOVA is a parametric hypothesis test that compares the adjusted means of two or more independent groups while statistically controlling for one or more continuous covariates. By removing the portion of outcome variance explained by the covariate, ANCOVA increases statistical precision and produces fairer group comparisons. The method builds on the general linear model framework consolidated by Fisher in the early 1930s and is described comprehensively by Tabachnick and Fidell (2013). | Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error. | 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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