1. As the number of years of previous experience increases by one and all else remains constant, the employee's salary falls by approximately I 2. As the number of years employed increases by one and all else remains constant, the employee's salary increases by l 3. As the number of years of education increases by one and all else remains constant, the employee's salary increases by l 4. Male employees, on average, earn than female employees (assuming that they are comparable otherwise) I 5. As the number of others supervised increases by one and all else remains constant, the employee's salary increases by about I 6. Employees in the Sales department earn, on average, than those in the Engineering department. I 7. Who earns more -- males or females? E Males :3 Females 8. Employees in the Purchasing department earn, on average, than those in the Engineering department. 9. Employees in the Advertising department earn, on average, than those in the Engineering department. I Multiple Regression Exercise Partial Data Employee Salary Years Previous Experience) Years Employed Years Education Gender Department Number Supervised Depal Dept2 |Dept3|Dep14 1 $65 ,487 12 1 4 2 $4G.184 3 $32,782 4 $54 899 5 $34,869 6 135,487 NENWDANNEOOH 7 $26,548 $32,920 $29,548 $34,231 $23,654 $39,331 $36,512 Coded Variables Department 1= Sales Department 2 = Purchasing Department 3 = Advertising Department 4 = Engineering Gender 1 = Male Gender 0 = Female Output Multiple Regression for Salary Multiple Adjusted StEr of R-Square Summary R R-Square Estimate 0.9236 0.8531 0.8213 4649.95 Degrees of Sum of Mean of F-Ratio p-Value ANOVA Table Freedom Squares qua res Explained 4644 236107 580529513.3 26.8490