Total payable salary. Suppose that a sales company was recently opened in your town and has been functioning for nine months. It has a total of 15 permanent and part-time staff members. It records the past nine months’

total payable salary (in dollars) for all staffs together with the percentage of part-time staff who were paid by an hourly rate and the monthly salary (in dollars) for those staff members without a bachelor’s degree. Regression output modeling the total monthly payable salary with the percentage of part-time staff members, and the monthly salary of staff members without a bachelor’s degree gave the following result.

Regression Statistics Multiple R 0.9946 R Square 0.9892 Adjusted R Square 0.9856 Standard Error 680.9776 Observations 9 ANOVA df SS MS F Significance F Regression 2 253988576 126994288 273.8537 1.27237E-06 Residual 6 2782382.903 463730.484 Total 8 256770958.9 Variable Coefficient SE(Coeff) t-ratio P-value Intercept 112985.6519 16375.8293 6.8995 0.0005 PartTime% -4028.0937 191.8015 -21.0014 0.0000 SalNoBD 26.2815 12.3894 2.1213 0.0781

a) Write the regression equation.

b) How much of the variation in total monthly payable salary is accounted for by the model?

c) Explain in context what the coefficient of the part-timer percentage means.

d) The model shows that the monthly salary of the staff members without a bachelor’s degree has no effect on the company’s total monthly payable salary. Therefore, the company decides to hire more employees without a bachelor’s degree. Is it true that monthly salary for staff members without a bachelor’s degree is unrelated to the total payable monthly salary of the company?