Update Statistics authored by Jonathan Ehret's avatar Jonathan Ehret
......@@ -87,7 +87,13 @@ ActData <- filter(ActData, ! ParticipantID %in% excludedParticipants)
Normally you want to use the gathered data to proof that a factor you evaluated has a significant effect on the outcome.
For this I recommend the following article on how to apply repeated-measures ANOVAs in R,
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>
![image](uploads/38d6fe059e5966411b0de20f3c478f9c/image.png){width=500px}
# Plotting your data
......
......