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Use this tag to ask about the nature of nonparametric or parametric methods, or the difference between the two. Nonparametric methods generally rely on few assumptions about the underlying distributions, whereas parametric methods make assumptions that allow data to be described by a small number of parameters.
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Significant Friedman's Test, but non-significant post-hocs?
I have a sample of 25 in my within-subjects design, with my DV as error rates. The data contains a lot of zeros (i.e. no errors) and is highly negatively skewed, so I can't run the repeated-measure AN …