Comparing two tests with JASP
I'm a psychology student and this month I attended a statistics course: the professor asked us to create a 15-items test (5 options Likert-type scale for the answers) on Google Form, distribute it and then gather all the answers.
We imported the .xlsx file to Google Sheets and started calculating stuff such as Cronbach's Alpha, variance, means and so on. We eventually generated a graph but only to discover that the resulting data was not normally distributed: we had to replace 4 items (which were causing this data to be skewed) with 4 better items, re-distribute the test and re-generate a new .xlsx. This time the generated graph showed what looks more like a normal curve.
Old test graph:
New test graph:
Now we have to compare the old test with the new one using JASP. I know that we must use a non-parametric test here because we have a skewed set of data in one hand and a normally distributed data in the other hand, but I got kinda lost during the explaination. I'd go with T-Tests -> Paired Samples T-Test -> Wilcoxon Signed-Rank, but I honestly don't know how to correctly organize and insert the data at this point (should it be the right one) on JASP.
Bonus question: is there a way to know/calculate if a given curve (which looks kinda normal, like the newer one I got) can be considered normal or not?
Thanks in advance! I really appreciate your help.