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Wielowymiarowa regresja liniowa z wieloma zmiennymi×Test T² Hotellinga×
DziedzinaStatystykaStatystyka
RodzinaRegression modelHypothesis test
Rok powstania20071931
TwórcaJohnson & Wichern (textbook treatment); classical multivariate least squaresHarold Hotelling
TypMultivariate linear regressionMultivariate parametric mean comparison
Źródło pierwotneJohnson, 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 ↗
Inne nazwymultivariate 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
Pokrewne56
PodsumowanieMultivariate 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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ScholarGatePorównaj metody: Multivariate Regression · Hotelling's T² Test. Pobrano 2026-06-17 z https://scholargate.app/pl/compare