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2009 Sep 08
1
Unexpected behavior in friedman.test and ks.test
...dent variables (different blood analyses). Question was whether the data is normally distributed for each of the analyses and, hence, whether I can apply a parametric test or not. Once I had loaded the data in a dataframe (and it looks as expected), I ran: ks.test(myData$f1_A, pnorm) ks.test(myData$f8_A, pnorm) They give p-values of < 2.2e-16 (with ties) and 8.882e-16. The Excel Add-In gives p-values of? 0.0074491 and, respectively,?0.2730477 Here the difference is serious, like between highly significant non-normal for both f1 and f8 (R), or one non-normal and one normal (the Add-in). I fi...