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| Πολυμεταβλητή Ανάλυση Συνδιακύμανσης (MANCOVA)× | Διακριτική Ανάλυση× | Δοκιμή T² του Hotelling× | |
|---|---|---|---|
| Πεδίο | Στατιστική | Στατιστική | Στατιστική |
| Οικογένεια≠ | Hypothesis test | Latent structure | Hypothesis test |
| Έτος προέλευσης≠ | 1970 | 1936 | 1931 |
| Δημιουργός≠ | Extension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s | Ronald A. Fisher | Harold Hotelling |
| Τύπος≠ | Parametric multivariate mean comparison with covariate control | Supervised classification and dimension reduction | Multivariate parametric mean comparison |
| Θεμελιώδης πηγή≠ | 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 ↗ | Hotelling, H. (1931). The Generalization of Student's Ratio. Annals of Mathematical Statistics, 2(3), 360–378. link ↗ |
| Εναλλακτικές ονομασίες≠ | MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis | Hotelling T² Testi — Çok Değişkenli t-Testi, multivariate t-test, Hotelling T-squared |
| Συναφείς≠ | 5 | 4 | 6 |
| Σύνοψη≠ | 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. | 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. |
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