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| 공분산 다변량 분석 (MANCOVA)× | 일원 분산 분석× | Welch's t-test (unequal variances)× | |
|---|---|---|---|
| 분야 | 통계학 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1970 | 1925 | 1947 |
| 창시자≠ | Extension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s | Ronald A. Fisher | B. L. Welch |
| 유형≠ | Parametric multivariate mean comparison with covariate control | Parametric mean comparison | Parametric mean comparison (unequal variances) |
| 원전≠ | Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541 | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ | Welch, B. L. (1947). The generalization of Student's problem when several different population variances are involved. Biometrika, 34(1/2), 28–35. DOI ↗ |
| 별칭≠ | MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA | unequal variances t-test, Welch-Satterthwaite t-test, Welch t-Testi (Eşit Olmayan Varyans) |
| 관련≠ | 5 | 4 | 4 |
| 요약≠ | 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). | One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925. | 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. |
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