SUMMARY OUTPUT Regression Statistics Multiple R 0.94437 OUTPUT #1 R Square 0.891835 Adjusted R Square 0.852503 Standard Error 9.238469 Observations 16 ANOVA Significance df 5S MS F F Regression 4 7740.908 1935.227 22.6742 2.8BE-05 Residual 11 938.8424 85.34931 Total 15 8679.75 Standard Upper Coefficients Error t Stat P-value Lower 95% 95% Intercept 30.38008 23.61776 1.286323 0.224745 -21.6023 82.36243 Age 2.648546 0.314748 8.414803 4.03E-06 1.955789 3.341302 Evaluation 4.25907 4.046897 -1.05243 0.315172 -13.1662 4.648086 MBA 7.602463 5.768718 1.317877 0.021433 -5.0944 20.29933 Certificate -1.47282 6.549622 -0.68291 0.50879 -18.8884 9.942803MULTIPLE REGRESSION 1. Management wanted to study executive salary during their tenure with the company. It was hypothesized that salary can be predicted based on an individual's age, annual evaluation score, and education. Education consist of three levels. (i) Six months training. (ii) 18 months certificate program. (ili) MBA. Only one of these levels applies to an executive (so 18 months program overwrites the 6 months training, and MBA overwrites both). To answer the following questions, observe Output 1 at the bottom of this exam. Use this output to answer questions 1-1 to 1-6. 1-1. When testing Betal(Age), the p-value = 4.06E-06. When testing Beta2(Evaluation) the p-value = 0.315. What do you conclude at 10% significance level? a. Linear relationship between Salary and Age is about 31% stronger then the linear relationship between Salary and Evaluation. b. Age is a predictor that does not add information to the model, but Evaluation does. c. Age is a predictor that adds information to the model, but Evaluation does not. d. Both predictors add information to the model at 10% significance level. 1-2. The coefficient of "Evaluation" is 4.259. This means that on the average the salary of an individual with evaluation score of X, is higher than the salary of an individual whose evaluation score is X-1 by 4259 dollars, provided they are at the same age. a. True b. False1-3. The interpretation of b3(for MBA) = 7.60 is: a. For every additional executive with an MBA degree, Salary increases by 7600 dollars a year. b. Every additional MBA degree an executive hold rewards the executive 7600 dollars a year c. None of the answers above is correct. 1-4. What is the difference between the expected annual salaries of an executive who hold an MBA degree and an executive who took the 18 months certificate program, if they are equal in all other variables? a. 4.259 thousand dollars b. 7.602 thousand dollars. C. (7.602 - 1.472) thousand dollars d. (7.602+1.472) thousand dollars 1-5. Can you argue with 5% significance level that there is indeed a significant difference between the annual salaries of an executive who took the 6-month training course, and an executive who took the certificate program, if they are at the same age and get the same evaluation score? a. No. Cannot make this argument b. Yes. There is sufficient evidence to make the argument. 1-6. Make a prediction of the salary for a 42 years old executive who took the 6-month training course, and received an evaluation score of 7.2. Show your calculation in the Answers sheet