Σύγκριση μεθόδων

	Δοκιμή T² του Hotelling	Πολυμεταβλητή Πολλαπλή Γραμμική Παλινδρόμηση
Πεδίο	Στατιστική	Στατιστική
Οικογένεια	Hypothesis test	Regression model
Έτος προέλευσης	1931	2007
Δημιουργός	Harold Hotelling	Johnson & Wichern (textbook treatment); classical multivariate least squares
Τύπος	Multivariate parametric mean comparison	Multivariate linear regression
Θεμελιώδης πηγή	Hotelling, H. (1931). The Generalization of Student's Ratio. Annals of Mathematical Statistics, 2(3), 360–378.	Johnson, R. A. & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis (6th ed.). Pearson. ISBN: 978-0131877153
Εναλλακτικές ονομασίες	Hotelling T² Testi — Çok Değişkenli t-Testi, multivariate t-test, Hotelling T-squared	multivariate multiple regression, MLR with multiple dependent variables, multiple-outcome regression, Çok Değişkenli Regresyon (MLR — Çoklu DV)
Συναφείς	6	5
Σύνοψη	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.	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.