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Test t pour échantillons indépendants×Analyse de la variance multivariée (MANOVA)×Régression linéaire multiple multivariée×
DomaineStatistiqueStatistiqueStatistique
FamilleHypothesis testHypothesis testRegression model
Année d'origine190819322007
Auteur d'origineStudent (W. S. Gosset)Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)Johnson & Wichern (textbook treatment); classical multivariate least squares
TypeParametric mean comparisonParametric multivariate mean comparisonMultivariate linear regression
Source fondatriceStudent (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574Johnson, R. A. & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis (6th ed.). Pearson. ISBN: 978-0131877153
Aliasstudent t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testiMultivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)multivariate multiple regression, MLR with multiple dependent variables, multiple-outcome regression, Çok Değişkenli Regresyon (MLR — Çoklu DV)
Apparentées455
RésuméThe 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.MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932.Multivariate regression is a linear regression method that predicts several continuous dependent variables at the same time from a shared set of predictors. As developed in standard treatments such as Johnson and Wichern's Applied Multivariate Statistical Analysis (2007), each response equation can be fitted by ordinary least squares while the covariance structure of the residuals is used for joint testing across outcomes.
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ScholarGateComparer des méthodes: Independent t-test · MANOVA · Multivariate Regression. Consulté le 2026-06-20 sur https://scholargate.app/fr/compare