Using the linear regression model from the original analysis, the professor calculates that the average residual from the students who took AP Statistics is 0.2414, while the average residual from the students who did not take AP Statistics is -0.1609. (e) Use the residual calculations to estimate how much greater the GPA for a student who takes AP Statistics in high school would be, on average, than the GPA for a student who does not take AP Statistics if the students study the same number of hours per week. The professor then creates two regression models, one for the students who take AP Statistics and one for the other students. The resulting regression equations are shown below. Linear Fit for Students who take AP Statistics in High School: Predicted GPA = 1.9427 + 0.0524(Hours) Linear Fit for Students who do not take AP Statistics in High School: Predicted GPA = 1.5396 + 0.0502 (Hours) (6) A 95% confidence interval for the true difference in the two slopes is 0.0022 0.0134. Based on this interval, is there a significant difference in the two slopes? Explain. (g) A 95% confidence interval for the true difference in the two y-intercepts is 0.4031