Test De Wilcoxon Anova. The ANOVA is somewhat robust to non-normality but not very. Only a multiple comparison method will be appropriate as a post-hoc test for Friedman ANOVA.
Additionally the Wilcoxon as with most rank based statistical tests are more powerful and increase in power with non-normal data. Like the t-test the Wilcoxon test comes in two forms one-sample and two-samples. However some fields tend to have a bias against distribution free statistical tests.
This can occur when when difference between repeated measurements are not normally distributed or if outliers exist.
For a repeated-measures design an individual is assessed on a measure on two occasions or under two conditions. THIS IS NOT THE CORRECT STATISTICAL ANALYSIS SINCE AN ANOVA FOR REPEATED MEASURES HAS TO BE CARRIED OUT MAYBE CONSIDERING ALSO SOME TRANSFORMATION OF THE VARIABLES. Each individual is a case in the SPSS data. This bias is founded in the tradition and NOT the math.
