Comparer des méthodes

	Analyse discriminante	Test t pour échantillons indépendants	Analyse de variance à un facteur
Domaine	Statistique	Statistique	Statistique
Famille	Latent structure	Hypothesis test	Hypothesis test
Année d'origine	1936	1908	1925
Auteur d'origine	Ronald A. Fisher	Student (W. S. Gosset)	Ronald A. Fisher
Type	Supervised classification and dimension reduction	Parametric mean comparison	Parametric mean comparison
Source fondatrice	Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.	Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25.	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.
Alias	LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis	student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Apparentées	4	4	4
Résumé	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.	The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances.	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.