A B D E F G H K 1 SUMMARY OUTPUT 2 3 Regression Statistics 4 Multiple R 0.230294 5 R Square 0.053035 6 Adjusted R 0.046658 7 Standard El 0.542438 8 Observation 300 9 10 ANOVA 11 df SS MS F ignificance F 12 Regression 2 4.894258 2.447129 8.316801 0.000306 13 Residual 297 87.38904 0.294239 14 Total 299 92.2833 15 16 Coefficients andard Errant Stat P-value Lower 95% Upper 95% ower 95.0%upper 95.0% 17 Intercept 3.866468 0.167768 23.04657 4.23E-68 3.536304 4.196632 3.536304 4.196632 18 beauty 0.157448 0.038618 4 4.077017 5.86E-05 0.081448 0.233448 0.081448 0.233448 19 age 0.002998 0.003383 0.886233 0.376209 -0.00366 0.009656 -0.00366 0.009656 20 21In this exercise we look again at the relationship between the look of instructors and their course evaluation. The dataset contains several variables, but for the purpose of this problem we are only considering course evaluations, beauty and age. Download the file at the following link. Open the file in Excel and estimate the following three linear regression models: (A) COURSE_EVAL = beta0 + beta1 * BEAUTY + error (B) COURSE_EVAL = beta0 + beta1 * AGE + error (C) COURSE_EVAL = beta0 + beta1 * BEAUTY + beta2 * AGE + error where: . COURSE_EVAL: average course evaluation of the instructor . BEAUTY: beauty index of the instructor (between -2 and 2 with 0 representing average look) . AGE: age (in years) of the instructors Answer the following questions: Vladimir and Igor are identical twins and they both happen to be teachers at the same university: based on model C, how much do you expect to be the difference in COURSE_EVAL between them? [X1] Mario and Luigi are longtime college friends from the class of 1960 and they now happen to be teachers at the same university; Mario has always been considered the better looking of the two with a BEAUTY index of 1.9 while Luigi's index is 1.5. Based on model C, Mario is expected to have (type HIGHER or LOWER) [X2] COURSE_EVAL relative to Luigi by [X3] What is the estimated effect of BEAUTY on COURSE_EVAL in regression A? [X4] , and in regression C? [X5]. Comparing the estimates for regression A and C, do you find evidence that regression A might suffer from omitted variable bias? (type YES or NO) [X6] Comparing the estimated effect of AGE on COURSE_EVAL in regression B and C: do you find evidence that regression B might suffer from omitted variable bias? (type YES or NO) [X7]. Is the statistical significance (at 5%) of AGE in the two regressions different? (type YES or NO) [X8] Professor Wang has a beauty index of -1.5 and is 54 year old. What is the predicted course evaluation by model C for Professor Wang? [X9] Which model would you recommend (type A, B, or C) [X10]