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Multivariate multiple lineare Regression×Hotelling's T²-Test×
FachgebietStatistikStatistik
FamilieRegression modelHypothesis test
Entstehungsjahr20071931
UrheberJohnson & Wichern (textbook treatment); classical multivariate least squaresHarold Hotelling
TypMultivariate linear regressionMultivariate parametric mean comparison
Wegweisende QuelleJohnson, R. A. & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis (6th ed.). Pearson. ISBN: 978-0131877153Hotelling, H. (1931). The Generalization of Student's Ratio. Annals of Mathematical Statistics, 2(3), 360–378. link ↗
Aliasnamenmultivariate multiple regression, MLR with multiple dependent variables, multiple-outcome regression, Çok Değişkenli Regresyon (MLR — Çoklu DV)Hotelling T² Testi — Çok Değişkenli t-Testi, multivariate t-test, Hotelling T-squared
Verwandt56
ZusammenfassungMultivariate 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.Hotelling's T² test is a multivariate parametric hypothesis test that simultaneously compares the mean vectors of two independent groups across multiple continuous outcome variables. It was introduced by Harold Hotelling in 1931 as the direct multivariate generalization of Student's t-test, replacing the scalar mean difference with a vector difference scaled by the pooled variance-covariance matrix.
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ScholarGateMethoden vergleichen: Multivariate Regression · Hotelling's T² Test. Abgerufen am 2026-06-17 von https://scholargate.app/de/compare