Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Kovariācijas analīze (ANCOVA)× | Neatkarīgo paraugu t-tests× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1932 | 1908 |
| Autors≠ | Ronald A. Fisher | Student (W. S. Gosset) |
| Tips≠ | Parametric group comparison with covariate control | Parametric mean comparison |
| Pirmavots≠ | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗ |
| Citi nosaukumi≠ | analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi) | student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi |
| 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). | The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances. |
| ScholarGateDatu kopa ↗ |
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