Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Kovariācijas analīze (ANCOVA)× | Velča t-tests (nevienādas dispersijas)× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1932 | 1947 |
| Autors≠ | Ronald A. Fisher | B. L. Welch |
| Tips≠ | Parametric group comparison with covariate control | Parametric mean comparison (unequal variances) |
| Pirmavots≠ | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Welch, B. L. (1947). The generalization of Student's problem when several different population variances are involved. Biometrika, 34(1/2), 28–35. DOI ↗ |
| Citi nosaukumi | analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi) | unequal variances t-test, Welch-Satterthwaite t-test, Welch t-Testi (Eşit Olmayan Varyans) |
| Saistītās | 4 | 4 |
| Kopsavilkums≠ | ANCOVA is a parametric hypothesis test that compares the adjusted means of two or more independent groups while statistically controlling for one or more continuous covariates. By removing the portion of outcome variance explained by the covariate, ANCOVA increases statistical precision and produces fairer group comparisons. The method builds on the general linear model framework consolidated by Fisher in the early 1930s and is described comprehensively by Tabachnick and Fidell (2013). | Welch's t-test is a parametric hypothesis test that compares the means of two independent groups without assuming their variances are equal. It was introduced by B. L. Welch in 1947 as a more robust generalization of Student's two-sample test for situations where the two groups have different spread. |
| ScholarGateDatu kopa ↗ |
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