Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Teste T² de Hotelling× | Regressão por Mínimos Quadrados Ordinários (MQO)× | |
|---|---|---|
| Área≠ | Estatística | Econometria |
| Família≠ | Hypothesis test | Regression model |
| Ano de origem≠ | 1931 | 2019 |
| Autor original≠ | Harold Hotelling | Wooldridge (textbook treatment); classical least squares |
| Tipo≠ | Multivariate parametric mean comparison | Linear regression |
| Fonte seminal≠ | 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 |
| Outros nomes≠ | 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 |
| Relacionados≠ | 6 | 5 |
| Resumo≠ | 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). |
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