Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Divu faktoru dispersijas analīze (Divu faktoru ANOVA)× | Kovariācijas analīze (ANCOVA)× | Daudzvarianto dispersijas analīze (MANOVA)× | |
|---|---|---|---|
| Nozare | Statistika | Statistika | Statistika |
| Saime | Hypothesis test | Hypothesis test | Hypothesis test |
| Izcelsmes gads≠ | 1925 | 1932 | 1932 |
| Autors≠ | Ronald A. Fisher | Ronald A. Fisher | Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.) |
| Tips≠ | Parametric factorial mean comparison | Parametric group comparison with covariate control | Parametric multivariate mean comparison |
| Pirmavots≠ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478 | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 |
| Citi nosaukumi≠ | factorial ANOVA, two-factor ANOVA, İki Yönlü ANOVA | analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi) | Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA) |
| Saistītās≠ | 6 | 4 | 5 |
| Kopsavilkums≠ | Two-Way ANOVA is a parametric hypothesis test that simultaneously examines the main effects of two independent categorical factors and their interaction effect on a single continuous dependent variable. The technique was developed within the broader framework of the analysis of variance established by Ronald A. Fisher in 1925 and remains the standard approach whenever an experiment or survey includes exactly two between-subjects factors. | 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). | MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932. |
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