@@ -89,7 +89,7 @@ Normally you want to use the gathered data to proof that a factor you evaluated
For this I recommend the following article on how to apply repeated-measures ANOVAs in R: https://www.datanovia.com/en/lessons/repeated-measures-anova-in-r/
In general, you should check perform performing paramteric test (like ANOVA or t-tests) that your data is actually normally distributed and fullfills the requirements (see website above) and otherwise use a non-parametric test should be used (*text books have an exclusion for this for large numbers (Central Limit Theorem), which often refers to 30 being a large enough number*). Otherweise check this graph for which tests might be useful (taken from the second book under Further Reading):<br>
In general, you should check before performing paramteric test (like ANOVA or t-tests) that your data is actually normally distributed and fullfills the requirements (see website above) and otherwise use a non-parametric test (*text books have an exclusion for this for large numbers (Central Limit Theorem), which often refers to 30 being a large enough number*). Otherweise check this graph for which tests might be useful (taken from the second book under Further Reading):<br>
Another database for statistical knowledge and a more interactive version of the diagram above can be found at https://www.methodenberatung.uzh.ch/de.html (unfortunately only in German)
