Sammenlign metoder

	Robust Friedman Test	Friedman-test
Fagområde	Statistik	Statistik
Familie	Hypothesis test	Hypothesis test
Oprindelsesår	1990s–2000s	1937
Ophavsperson	Extension of Friedman (1937); robust variants developed by Wilcox and colleagues	Milton Friedman
Type	Robust nonparametric repeated measures comparison	Nonparametric repeated-measures comparison (by ranks)
Oprindelig kilde	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838	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.
Aliasser	robust rank-based repeated measures test, trimmed-mean Friedman test, Friedman test with robust estimation, Fried-type robust test	Friedman two-way analysis of variance by ranks, Friedman rank test, Friedman Testi
Relaterede	6	2
Resumé	The robust Friedman test is a nonparametric procedure for comparing three or more related (within-subjects) conditions that replaces standard ranking or mean-based summaries with robust location estimates — typically trimmed means or Winsorized statistics — to reduce the influence of outliers and heavy-tailed distributions on the inference.	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.