Comparer des méthodes

	MANCOVA (Analyse Multivariée de la Covariance)	Analyse discriminante
Domaine	Statistique	Statistique
Famille	Hypothesis test	Latent structure
Année d'origine	1970	1936
Auteur d'origine	Extension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s	Ronald A. Fisher
Type	Parametric multivariate mean comparison with covariate control	Supervised classification and dimension reduction
Source fondatrice	Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541	Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.
Alias	MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis
Apparentées	5	4
Résumé	MANCOVA (Multivariate Analysis of Covariance) is a parametric hypothesis test that simultaneously compares two or more groups on multiple continuous dependent variables while statistically controlling for one or more covariates. It extends MANOVA by incorporating covariate adjustment, a tradition consolidated in multivariate statistical methodology by the 1970s and authoritatively documented by Tabachnick and Fidell (2019).	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.