Hello group,
I have performed a simple experiment (and got the data). Now it is time to find out if the results are stat. significant. I would prefer a non-parametric test since less assumptions are required to hold.
I have one IV (system) with two possible categories (system A and system B). My null hypothesis is that both systems cause the same effect on participants. The outcome variable are a number of relevance ratings (on a 6 point scale S={1,2,3,4,5,6}) from users that used system A and a number of relevance ratings from the same users that used system B. The number of relevance ratings users did was up to them and can be different for system A and system B. An extract of the data looks like this:
User System Rating
1 A 2
1 A 1
1 A 3
1 B 4
1 B 6
2 B 5
2 B 6
2 A 2
2 A 1
2 B 6
...
It is important to point out that half of the users have first used System A and then system B to solve the task. The other half of the users have done the opposed order.
Since both systems have been counterbalanced, I would assume that the Mann-Whitney test should be my choice.
However, I also have used the same people on the test and that would formally ask for a Wilcoxon Matched Pairs Test.
I would like to know what the experts here think about that.
Best Regards,
Karl
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