ScholarGate
Pembantu

Bandingkan kaedah

Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.

Ujian T² Hotelling×Regresi Linear Berganda Pelbagai Pemboleh Ubah×
BidangStatistikStatistik
KeluargaHypothesis testRegression model
Tahun asal19312007
PengasasHarold HotellingJohnson & Wichern (textbook treatment); classical multivariate least squares
JenisMultivariate parametric mean comparisonMultivariate linear regression
Sumber perintisHotelling, H. (1931). The Generalization of Student's Ratio. Annals of Mathematical Statistics, 2(3), 360–378. link ↗Johnson, R. A. & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis (6th ed.). Pearson. ISBN: 978-0131877153
AliasHotelling T² Testi — Çok Değişkenli t-Testi, multivariate t-test, Hotelling T-squaredmultivariate multiple regression, MLR with multiple dependent variables, multiple-outcome regression, Çok Değişkenli Regresyon (MLR — Çoklu DV)
Berkaitan65
RingkasanHotelling'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.
ScholarGateSet data
  1. v1
  2. 1 Sumber
  3. PUBLISHED
  1. v1
  2. 1 Sumber
  3. PUBLISHED

Pergi ke carian Muat turun slaid

ScholarGateBandingkan kaedah: Hotelling's T² Test · Multivariate Regression. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare