Hi all,

The Kruskal-Wallis test is a generalization of the two-sample Mann-Whitney
test to *k* samples.  That being the case, the Kruskal-Wallis test with *k*=2
should give an identical p-value to the Mann-Whitney test, should it not?

x1<-c(1:5)
x2<-c(6,8,9,11)
a<-wilcox.test(x1,x2,paired=FALSE)
b<-kruskal.test(list(x1,x2),paired=FALSE)
a$p.value
[1] 0.01587302
b$p.value
[1] 0.01430588

The p-values are slightly different (note that there are no ties in the
data, so computed p-values should be exact).

Can anyone explain the discrepancy?  It's been awhile since I studied
nonparametric stats and this one has me scratching my head.

Many thanks!
Tom

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