1. The following data were obtained from 7 students from an introductory statistics class. Students reported the number of hours of sleep they had last night (X) and their exam grades the following morning (Y). The correlation between hours of sleep and exam grade is r(5) = .88, p < .05

Hours Sleep (X)	Exam Grade (Y)
3	65
2	68
5	75
6	82
7	89
8	91
6	96

1. Calculate the slope for the regression equation where the number of hours of sleep a student had (X) predicts their exam grade (Y). Please copy/paste your Google Sheets calculations below [20pts]

1. Calculate the intercept for the regression equation where the number of hours of sleep a student had (X) predicts their exam grade (Y). [6pts]
2. Write out the complete regression equation you calculated for the number of hours of sleep (X) predicting exam grade (Y). [6pts]

1. How would you interpret the slope in your regression equation, in other words, what does this value mean? [8pts]

1. How would you interpret the intercept in your regression equation, in other words, what does this value mean? [8pts]

1. If a student had 4 hours of sleep what is their predicted exam grade? [6pts]

2. The correlation between hours of sleep and exam grade is r(5) = .88, p < .05. What statistic can be used to determine the proportion of variability that the hours of sleep a student has can explain their exam grade? What would this value be for the current example? [8pts]

3. Suppose the correlation between anxiety and depression is .23, and the correlation between exercise and depression is -.29. If a simple linear regression were conducted with anxiety predicting depression, and again for exercise predicting depression, which predictor would account for more variability in depression? Please explain why. [8]