The task is to predict outcomes based on previous outcomes. On every trial the subject tries to predict the outcome as good as possible and learns to adapt the prediction through the prediction error (difference between predicted and actual outcome). In one condition (say the easy one), outcomes change slowly, in the other condition (the hard one) outcomes change very often and the subject has to frequently update the prediction.

Data could look like this:

Prediction Error

cond1/ cond2

10 / 44

24 / 31

54 / 3

34 / 20

2 / 20

4 / 15

I want to compare the mean of the prediction error of the two conditions.

As the subject runs through both conditions, one would use a paired sample t-test. However, the trials of both condition are not strictly related (in the sense that one is a pre- and the other is a post-treatment test). The outcomes are pseudo-randomly generated and therefore, outcomes in the conditions are not strictly paired.

My question is: do I have to use a paired sample t-test and if so, why not an independent measures t-test.

Any suggestions are welcomed!

Monstera