I have a small dataset that was gathered from 1 subject during 1 “session”. At the beginning of the session, the subject performed a movement task for approximately 40 seconds, and completed about 20 repetitions of the movement during that time.
Approximately 1 hour later, at the end of the session, the subject once again performed the movement task. This time, the subject performed the task for about 170 seconds and completed several more movement repetitions.
With each repetition of the movement we obtain a single number that represents the “force” used by the subject during that repetition.
Therefore, my small dataset consists of:
- about 20 reps from timepoint 1, each with an associated amount of force, over a 40 second period
- about 70 reps from timepoint 2, each with an associated force, over a 170 second period.
I want to see if the average force exerted by this 1 subject at timepoint 2 is significantly lower than the average force at timepoint 1.
My inclination was to use a paired t-test, but that’s impossible since a paired t-test requires matched samples.
I could “truncate” the number of samples at timepoint 2 so that it is equal to the number of samples at timepoint 1, but it’s still not truly matching the samples.
For the time being I’ve just done an unpaired t-test to compare the samples, but I’m curious what is the “correct” way to handle a sample like this.