dom) Emphasis 15. A researcher is interested to know whether class attendance affects the outcome of a final exam among college students. The researcher obtains the following OLS estimates: Final 18-0.017 attendance +3.23 priGPA (0.96) (0.034) (0.34) Sample size (n) 680; R2= 0.134 (1) Where final is the score of the student in the final exam, attendance is the percentage of classes the student attended, and priGPA is the prior college grade point average. For example, for a student in the fourth semester, priGPA measures his/her GPA of the first three semesters. Standard errors are in parentheses. a. Interpret the coefficient of attendance. Is this coefficient statistically significant? Explain your answer. [7 marks) b. The researcher controls for the nonlinear effect of priGPA on final and obtains the following estimates: Final 32 0.008 attendance-8.98 priPA +2.3 priGPA (2) (2.9) (0,033) (2.29) n-680; R0.169 (0.42) Is there evidence for increasing marginal returns to prGPA? In one or two sentences explain what the increasing marginal returns mean in this example. 18 marks] The researcher decides to control for ability by adding the ACT test score to the model and obtains the following results Final 22 0.089 attendance-8.98 priGPA 2.3 priGPA +0.36ACT (3.2) (0.035) (223) (0.42) n-680: R 0.222 (3) (0.05) Explain the effect of adding ACT on the standard error of attendance L1000 Introduction to Econometrics (8 marks) d And finally, the researcher wants to test whether his estimates suffer from heteroscedasticity. Use the auxillary regression below to test for the presence of heteroscedasticity, is the squared of the estimated residuals from model (4) above. Final and Final are the predicted values of final score and the squared predicted values of final score, respectively 7 markal 050.22-5.57 Fal -0.11 Final n-680; -0.003 (5) FOUE