A researcher conducts a t test for dependent means in which it is predicted that there will be a decrease in unemployment from before to after a particular job-skills training program. The cutoff "t" needed is -1.8333. The standard deviation of the distribution of means of change scores is 2.0 and the mean change score for the sample studied is an increase of 5.2.

What is the effect size?

To compute the effect size in this scenario, we can use Cohen's d, which is a commonly used measure of effect size for t tests.

Cohen's d is computed by dividing the mean difference between the two groups by the standard deviation of the two groups combined. In this case, since it is a dependent means t test, we only have one group, so we use the standard deviation of the distribution of means of change scores.

To calculate Cohen's d, we use the formula:

d = mean difference / standard deviation

In this case, the mean difference is an increase of 5.2 (since it is a decrease in unemployment), and the standard deviation of the distribution of means of change scores is 2.0. Plugging these values into the formula, we get:

d = 5.2 / 2.0

d = 2.6

So, the effect size (Cohen's d) for this t test is 2.6.