Treat the data as if the scores are from an independent-measures study using two separate samples, each with n 5 7 participants. Compute the pooled variance, the estimated standard error for the mean difference, and the independent-measures t statistic. Using a 5 .05, is there a significant difference between the two sets of scores?

Exercise is known to produce positive psychological effects. Interestingly, not all exercise is equally effective. It turns out that exercising in a natural environment (e.g., jogging in the woods) produces better psychological outcomes than exercising in urban environments or in homes (Mackay & Neill, 2010). Suppose that a sports psychologist is interested in testing whether there is a difference between exercise in nature and exercise in the lab with respect to post-exercise anxiety levels. The researcher recruits n 5 7 participants who exercise in the lab and exercise on a nature trail. The data below represent the anxiety scores that were measured after each exercise session.

1. Treat the data as if the scores are from an independent-measures study using two separate samples, each with n 5 7 participants. Compute the pooled variance, the estimated standard error for the mean difference, and the independent-measures t statistic. Using a 5 .05, is there a significant difference between the two sets of scores?
2. Now assume that the data are from a repeated measures study using the same sample of n 5 7 participants in both treatment conditions. Compute the variance for the sample of difference scores, the estimated standard error for the mean difference, and the repeated-measures t statistic. Using a 5 .05, is there a significant difference between the two sets of scores?