Hope this is not too basic:
I understand we used paired testing in situations where, e.g., the same subject is tracked before- and after- an experiment/treatment, e.g., before- and after patient receives a medication.
But there are cases that are not described in this format, so I would like to know if dependence of events tested are enough to use paired tests. Specifically, I am thinking of these 2 experiments:
1)We are testing the parking times for cars C1, C2 of different makes ; we want to see if mean parking times are equal.
We have 10 people park car C1 and we measure parking times for each, we compute the mean $ \mu_1 $ of all parking times. We then have the same 10 people park car C2 in the same spot as C1 , measure parking times, compute the mean $ \mu_2 $. Since parking jobs are done each time by the same group, do we then use paired t-Test to test whether $\mu_1= \mu_2$ ( at a given choice of confidence) , since/because the two times are correlated?
2)We want to test whether right- and left- limbs are of equal length. Do we use paired testing If the limbs are measured in the same person, because the measurememnts are likely correlated ? And if some of the cases we only measured only one limb in one person and left limb in another or we only measured one limb per person we would not used pair testing? Thanks.