2. (4 points) Adapt the codes we used in Lecture 5 for College GPA prediction (codeeviewsGPA2.prg) to do a prediction using a model that uses the college GPA (colgpa) on the left hand side and in addition to the high school percentile ranking (hsperc) and SAT score (sat) variables we used in class, it also uses the athlete status (athlete) and gender (female). Make a point prediction and a 99% confidence interval for two individuals: a. Person 1: man, non-athlete, in the 60% of high school percentile ranking, and a SAT score equal to 1100. b. Person 2: woman, athlete, in the 10% of high school percentile ranking, and a SAT score equal to 1550. The code you write (again, adapting from what we've used in class) should read the raw data, run the regression and do the prediction, including the confidence intervals using the formula on the slides. (You can remove the part of the code that produces the initial data plots.) Upload the code to ELMS and also copy the code to your write-up. In your write-up report the point estimate and the confidence interval you find. 3. (2 points) Using the same data, answer the following question. You do not need to write a code to do this, but you need show the regression output you use to answer the question. Controlling for high school percentile, does being a woman change how one's SAT affects one's college GPA? (In other words, would a 1 unit change in SAT have the same effect on college GPA for women and men?)