8. Using the X (10) & the Y (GPA) data, compute the Pearson=5 correlation coefficient (create a table for your calculations). Is there a relationship? What kind of relationship? How strong? Explain the relationship between the two variables, if any. 9. Using regression formula #1 on the formula sheet, calculate the regression equation for the two variables, X (IQ) and Y (GPA). Interpret the significance of the slope constant and the Y-intercept in the regression equation. 10. Using the regression equation, compute the predicted Y= (GPA) value obtained for each X (1Q) value (put data into a table). 11. If you were an admission officer looking at this data relationship and you were interested in students who would succeed at your graduate school, what IQ score cut-off policy would you institute for admission decisions to insure adequate academic performance of your students at your school. Explain how you chose where to make the admission cut based on IQ scores. What minimum GPA would your IQ cut-off score predict