Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Hotellinga T² tests× | Daudzvariāciju daudzkārtējā lineārā regresija× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime≠ | Hypothesis test | Regression model |
| Izcelsmes gads≠ | 1931 | 2007 |
| Autors≠ | Harold Hotelling | Johnson & Wichern (textbook treatment); classical multivariate least squares |
| Tips≠ | Multivariate parametric mean comparison | Multivariate linear regression |
| Pirmavots≠ | Hotelling, 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 |
| Citi nosaukumi≠ | 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) |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | 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. |
| ScholarGateDatu kopa ↗ |
|
|