Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Daudzvarianto kovariācijas analīze (MANCOVA)× | Lineārā diskriminantā analīze× | |
|---|---|---|
| Nozare | Statistika | Statistika |
| Saime≠ | Hypothesis test | Latent structure |
| Izcelsmes gads≠ | 1970 | 1936 |
| Autors≠ | Extension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s | Ronald A. Fisher |
| Tips≠ | Parametric multivariate mean comparison with covariate control | Supervised classification and dimension reduction |
| Pirmavots≠ | Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541 | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗ |
| Citi nosaukumi | MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis |
| Saistītās≠ | 5 | 4 |
| Kopsavilkums≠ | MANCOVA (Multivariate Analysis of Covariance) is a parametric hypothesis test that simultaneously compares two or more groups on multiple continuous dependent variables while statistically controlling for one or more covariates. It extends MANOVA by incorporating covariate adjustment, a tradition consolidated in multivariate statistical methodology by the 1970s and authoritatively documented by Tabachnick and Fidell (2019). | Discriminant analysis finds linear combinations of predictor variables that best separate two or more known groups. It is used both to understand which predictors distinguish the groups and to classify new observations into those groups with minimum error. |
| ScholarGateDatu kopa ↗ |
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