[Solution] A regression model was produced by an analyst to investigate the effect of Age, Years-of Service, and Years-of-Education on Wages (measured in
Question: A regression model was produced by an analyst to investigate the effect of Age, Years-of Service, and Years-of-Education on Wages (measured in thousands of dollars per year) paid to employees in a particular industry. The model output based on a sample of 200 workers indicates the following:
• The R2 value (coefficient of determination) is 0.76
• The associated F statistic and p-value of the F are 28.67 and 0.0005 respectively
• The standard error of the estimate is 3.96
• Coefficient values and the associated p-values for hypothesis testing are as follows
| Coefficients | P-value | |
| Intercept | 14.85 | 0.04 |
| Education | 6.83 | 0.03 |
| Service | 2.04 | 0.001 |
| Age | -0.17 | 0.025 |
- What are the independent and dependent variables in the model? Formulate the regression equation.
- What are your expectations about the correlations between each independent variable and the dependent variable? Why?.
- How would you evaluate the model? Is it any good? Why or why not? (5)
- There is a charge that age based wage discrimination occurs in this industry. How would you respond to this charge based on the regression model results? (7)
- Construct a 95% confidence interval prediction of the wages earned by a 35 year old employee with 8 years of education and 5 years of service. (7)
Deliverable: Word Document 