방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 다변량 분산 분석 (MANOVA)× | 판별 분석× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열≠ | Hypothesis test | Latent structure |
| 기원 연도≠ | 1932 | 1936 |
| 창시자≠ | Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.) | Ronald A. Fisher |
| 유형≠ | Parametric multivariate mean comparison | Supervised classification and dimension reduction |
| 원전≠ | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Fisher, R. A. (1936). The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188. DOI ↗ |
| 별칭≠ | Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA) | LDA, Fisher discriminant analysis, discriminant function analysis, canonical discriminant analysis |
| 관련≠ | 5 | 4 |
| 요약≠ | 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. | 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. |
| ScholarGate데이터셋 ↗ |
|
|