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Multivariate Meervoudige Lineaire Regressie×T²-toets van Hotelling×
VakgebiedStatistiekStatistiek
FamilieRegression modelHypothesis test
Jaar van ontstaan20071931
GrondleggerJohnson & Wichern (textbook treatment); classical multivariate least squaresHarold Hotelling
TypeMultivariate linear regressionMultivariate parametric mean comparison
Oorspronkelijke bronJohnson, 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 ↗
Aliassenmultivariate 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
Verwant56
SamenvattingMultivariate 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 vergelijken: Multivariate Regression · Hotelling's T² Test. Geraadpleegd op 2026-06-17 via https://scholargate.app/nl/compare