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| 정렬 순위 변환 분산 분석 (ART-ANOVA)× | Welch 분산 분석× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 2011 | 1951 |
| 창시자≠ | Wobbrock, Findlater, Gergle & Higgins | B. L. Welch |
| 유형≠ | Nonparametric factorial hypothesis test | Parametric mean comparison (heteroscedastic) |
| 원전≠ | Wobbrock, J. O., Findlater, L., Gergle, D., & Higgins, J. J. (2011). The aligned rank transform for nonparametric factorial analyses using only ANOVA procedures. Proceedings of the ACM CHI Conference on Human Factors in Computing Systems (CHI 2011), 143–146. DOI ↗ | Welch, B.L. (1951). On the Comparison of Several Mean Values. Biometrika, 38(3/4), 330–336. link ↗ |
| 별칭≠ | ART-ANOVA, aligned ranks ANOVA, nonparametric factorial ANOVA, Hizalanmış Sıra Dönüşümü ANOVA (ART-ANOVA) | Welch's F-test, heteroscedastic one-way ANOVA, Welch ANOVA — Heterojen Varyans ANOVA |
| 관련≠ | 7 | 3 |
| 요약≠ | The Aligned Rank Transform ANOVA (ART-ANOVA) is a nonparametric factorial hypothesis test that detects main effects and interactions in designs with two or more independent variables, without requiring normality. The procedure was formalized by Wobbrock, Findlater, Gergle, and Higgins in their 2011 CHI paper and operates by separately aligning each effect before ranking, so that standard ANOVA machinery can be applied to nonparametric data. | Welch ANOVA is a parametric hypothesis test that compares the means of three or more independent groups when their variances are not equal. Introduced by B. L. Welch in 1951, it replaces classic one-way ANOVA whenever the homogeneity-of-variance assumption fails, while still requiring approximately normal data. |
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