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b) Data was collected on 344 corporate executives to find out the effect of MBA degree and work experience on their salary. The following model was estimated: = 2.3501 + 3.6306D - 2.6354 D2i + 0.8527 X; + 1.634 (D, * X); Y t = R? = 0.8968 (1.263) (2.1805) (- 3.457) (7.605) (2.98) Y: Annual Income in Lakhs of Rupees Di and D2 are MBA and gender dummies respectively X: Work experience in years DI = 1 if one has MBA degree = 0 otherwise D2 = 1 for a female executive = 0 for a male executive i. Write the regression equations for female MBA executives and male MBA executives separately. i. Find the mean income level for the reference category and interpret it. i. Test the statistical significance of differential intercept coefficient between female MBA executives and Male MBA executives at 5% level of significance. . Interpret the coefficient of Di*Xi. . Now suppose out of this sample of 344 executives, 48 are female MBA executives and 156 are male MBA executives. To find out the relation between income earned and work experience, we run three regressions and the results obtained are as follows: Regression A: 156 male MBA executives, RSSA = 3.701 Regression B: for 48 female MBA executives, RSSB = 4.803 Pooled Regression: with 204 (156 male + 48 female) executives, RSs' = 9.7602

b) Data was collected on 344 corporate executives to find out the effect of MBA degree and work experience on their salary. The following model was estimated: = 2.3501 + 3.6306D - 2.6354 D2i + 0.8527 X; + 1.634 (D, * X); Y t = R? = 0.8968 (1.263) (2.1805) (- 3.457) (7.605) (2.98) Y: Annual Income in Lakhs of Rupees Di and D2 are MBA and gender dummies respectively X: Work experience in years DI = 1 if one has MBA degree = 0 otherwise D2 = 1 for a female executive = 0 for a male executive i. Write the regression equations for female MBA executives and male MBA executives separately. i. Find the mean income level for the reference category and interpret it. i. Test the statistical significance of differential intercept coefficient between female MBA executives and Male MBA executives at 5% level of significance. . Interpret the coefficient of Di*Xi. . Now suppose out of this sample of 344 executives, 48 are female MBA executives and 156 are male MBA executives. To find out the relation between income earned and work experience, we run three regressions and the results obtained are as follows: Regression A: 156 male MBA executives, RSSA = 3.701 Regression B: for 48 female MBA executives, RSSB = 4.803 Pooled Regression: with 204 (156 male + 48 female) executives, RSs' = 9.7602

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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b) Data was collected on 344 corporate executives to find out the effect of MBA degree and work experience on their salary. The following model was estimated: Y; = 2.3501 + 3.6306D, – 2.6354 D2i + 0.8527 X; + 1.634 (D, * X); t = (1.263) (2.1805) (- 3.457) (7.605) (2.98) R? = 0.8968 Y: Annual Income in Lakhs of Rupees Di and D2 are MBA and gender dummies respectively X: Work experience in years DI = 1 if one has MBA degree = 0 otherwise D2 = 1 for a female executive = 0 for a male executive i. Write the regression equations for female MBA executives and male MBA executives separately. ii. Find the mean income level for the reference category and interpret it. iii. Test the statistical significance of differential intercept coefficient between female MBA executives and Male MBA executives at 5% level of significance. iv. Interpret the coefficient of Di*Xi. v. Now suppose out of this sample of 344 executives, 48 are female MBA executives and 156 are male MBA executives. To find out the relation between income earned and work experience, we run three regressions and the results obtained are as follows: Regression A: Regression B: 156 male MBA executives, RSSA = 3.701 for 48 female MBA executives, RSSB = 4.803 Pooled Regression: with 204 (156 male + 48 female) executives, RSs' = 9.7602
Transcribed Image Text:b) Data was collected on 344 corporate executives to find out the effect of MBA degree and work experience on their salary. The following model was estimated: Y; = 2.3501 + 3.6306D, – 2.6354 D2i + 0.8527 X; + 1.634 (D, * X); t = (1.263) (2.1805) (- 3.457) (7.605) (2.98) R? = 0.8968 Y: Annual Income in Lakhs of Rupees Di and D2 are MBA and gender dummies respectively X: Work experience in years DI = 1 if one has MBA degree = 0 otherwise D2 = 1 for a female executive = 0 for a male executive i. Write the regression equations for female MBA executives and male MBA executives separately. ii. Find the mean income level for the reference category and interpret it. iii. Test the statistical significance of differential intercept coefficient between female MBA executives and Male MBA executives at 5% level of significance. iv. Interpret the coefficient of Di*Xi. v. Now suppose out of this sample of 344 executives, 48 are female MBA executives and 156 are male MBA executives. To find out the relation between income earned and work experience, we run three regressions and the results obtained are as follows: Regression A: Regression B: 156 male MBA executives, RSSA = 3.701 for 48 female MBA executives, RSSB = 4.803 Pooled Regression: with 204 (156 male + 48 female) executives, RSs' = 9.7602
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