পদ্ধতির তুলনা করুন

	Robust Friedman Test	রোবাস্ট রিপিটেড মেজারস অ্যানোভা (Robust Repeated Measures ANOVA)
ক্ষেত্র	পরিসংখ্যান	পরিসংখ্যান
পরিবার	Hypothesis test	Hypothesis test
উদ্ভবের বছর	1990s–2000s	1990s–2000s
প্রবর্তক	Extension of Friedman (1937); robust variants developed by Wilcox and colleagues	Rand R. Wilcox
ধরন	Robust nonparametric repeated measures comparison	Robust parametric mean comparison
মৌলিক উৎস	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838	Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Academic Press. ISBN: 978-0123869838
অপর নাম	robust rank-based repeated measures test, trimmed-mean Friedman test, Friedman test with robust estimation, Fried-type robust test	robust within-subjects ANOVA, trimmed-mean repeated measures ANOVA, robust RM-ANOVA, heteroscedastic repeated measures ANOVA
সম্পর্কিত	6	6
সারসংক্ষেপ	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.	Robust repeated measures ANOVA tests whether population trimmed means differ across three or more repeated conditions or time points measured on the same subjects. By replacing ordinary means with 20% trimmed means and replacing variances with Winsorized estimates, it maintains acceptable Type I error and power when data are non-normal, skewed, or contain outliers — conditions under which classical repeated measures ANOVA routinely breaks down.