Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| T²-критерій Хотеллінга× | Регресія звичайно найменших квадратів (ЗНК)× | |
|---|---|---|
| Галузь≠ | Статистика | Економетрика |
| Родина≠ | Hypothesis test | Regression model |
| Рік появи≠ | 1931 | 2019 |
| Автор методу≠ | Harold Hotelling | Wooldridge (textbook treatment); classical least squares |
| Тип≠ | Multivariate parametric mean comparison | Linear regression |
| Основоположне джерело≠ | Hotelling, H. (1931). The Generalization of Student's Ratio. Annals of Mathematical Statistics, 2(3), 360–378. link ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Інші назви≠ | Hotelling T² Testi — Çok Değişkenli t-Testi, multivariate t-test, Hotelling T-squared | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | 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. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
| ScholarGateНабір даних ↗ |
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