Friedman test and its use case.

hard

Answer

$Non-parametric alternative to repeated-measures ANOVA.$
$Same subjects rated on k treatments; rank within each subject, sum ranks per treatment.$
$Null: no treatment effect.$
$Useful for within-subject designs where normality is violated.$
$Follow-up: pairwise Wilcoxon with correction.$
$Common in ML benchmarking (rank algorithms across datasets).$

Check yourself — multiple choice

Independent samples
Non-parametric repeated-measures ANOVA: within-subject ranks across k treatments; used in benchmarking ML algos across datasets
Same as chi-square
Not real

Friedman: non-param repeated-measures ANOVA on within-subject ranks.

#hypothesis-testing#non-parametric

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