Recall that in exercise 50 the personnel director for Electronics Associates developed the following estimated regression equation relating an employee's score on a job satisfaction test to length of service and wage rate.
= 14.41 - 8.69x1 + 13.52x2
where
x1 = wage rate (dollars)
x2 = length of service (years)
y = job satisfaction test score (higher scores indicate greater job satisfaction)
A portion of the Minitab computer output follows.

a. Complete the missing entries in this output.
b. Compute F and test using a = .05 to see whether a significant relationship is present.
c. Did the estimated regression equation provide a good fit to the data? Explain.
d. Use the t test and a = .05 to test H0: β1 = 0 and H0: β2 = 0.

Analysis of Variance Source Regression X1 X2 Error Total DF Adj SS Adj MS F-Value P-Value 0.003 0.003 0.001 1 1 444.58 598.57 444.58 598.57 71.18 720.00 31.23 42.05 7 Model Summary R-sq (adj) R-sq (pred) 69. 93% R-sq 3.773 Coefficients Term VIF Coef 14.41 SE Coef 8.191 1.555 2.085 T-Value 1.76 P-Value Constant x2 Regression Equation 0.139 0.003 1.95 0.001 1.95 13.52 y- 14.41-8.69 X1 + 13.52 X2