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| 반복측정 분산분석× | 프리드만 검정× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1992 | 1937 |
| 창시자≠ | Girden (textbook treatment); Field (2013) | Milton Friedman |
| 유형≠ | Parametric within-subjects mean comparison | Nonparametric repeated-measures comparison (by ranks) |
| 원전≠ | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed., Ch. 14). SAGE. ISBN: 978-1446249185 | Friedman, M. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association, 32(200), 675–701. DOI ↗ |
| 별칭≠ | within-subjects ANOVA, repeated measures analysis of variance, rm-ANOVA, Tekrarlı Ölçüm ANOVA | Friedman two-way analysis of variance by ranks, Friedman rank test, Friedman Testi |
| 관련≠ | 4 | 2 |
| 요약≠ | Repeated-measures ANOVA is a parametric hypothesis test that compares three or more measurements taken from the same individuals — typically across time points or conditions — to decide whether their means differ. It extends one-way ANOVA to within-subjects designs, as treated in standard references such as Girden (1992) and Field (2013). | The Friedman test is a nonparametric hypothesis test that compares three or more related conditions measured on the same blocks or subjects, serving as the rank-based alternative to repeated-measures ANOVA. It was introduced by Milton Friedman in 1937 and works on ordinal or continuous data without assuming normality. |
| ScholarGate데이터셋 ↗ |
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