If paired scores are correlated highly (say, at r = .75) this means, compared to scores correlated weakly (say at r = .10), then the strongly correlated pairs ...Question 3Answera.... should not be used in a paired t-testb.... should each be tested for difference from zeroc.... will have more power in a paired t-testd.... should be added, rather than subtracted from each other

The correct answer is c. The pairs that are strongly correlated will have more power in a paired t-test.

Here's why:

A paired t-test is a statistical procedure used to determine whether the mean difference between two sets of observations is zero. In a paired sample t-test, each subject or entity is measured twice, resulting in pairs of observations.

The correlation coefficient (r) measures the strength and direction of the linear relationship between two variables. A high correlation (like r = .75) means that the variables are strongly related and change together at a high rate.

In the context of a paired t-test, a high correlation means that the difference scores (which are what you analyze in a paired t-test) will be more consistent (i.e., have a smaller standard deviation). This, in turn, makes the t-statistic larger, which makes the p-value smaller, which increases the power of the test.

In contrast, a low correlation (like r = .10) means that the variables are weakly related and do not change together consistently. This means that the difference scores will be less consistent (i.e., have a larger standard deviation), which makes the t-statistic smaller, the p-value larger, and the power of the test lower.

So, if you have a high correlation between paired scores, you will have more power in a paired t-test compared to if you have a low correlation.