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I am doing a Wilcoxon rank sum test (aka Wilcoxon-Mann-Whitney) with R. There are two variables "ScorePerView", that is metric and "HasCodeElement", that is binary.
So the syntax is like that
wilcox.test(ScorePerView ~ HasCodeElement, data=Datenmatrix, paired=FALSE, alternative='less')
When the result is significant (p-value < 0.005), then one distribution is lower or equal to the other.
But which one is lower? Is the one where HasCodeElement is 0 is lower (or equal) then the one where HasCodeElement is 1. Or is it the other way where HasCodeElement is 1 is lower (or equal) then the one where HasCodeElement is 0.
How can I interpret the R output on an one tailed test?
Here is my result with the syntax above.
Found the answer here: How do I interpret the Mann-Whitney U when using R's formula interface
Also marked the Question as duplicated.