Recall that in exercise 40 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.
y = 14.4 €“ 8.69x1 + 13.5x2
Where
x1 = length of service (years)
x2 = wage rate (dollars)
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 α = .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 α = .05 to test H0: β1 = 0 and H0: β2 =0.

The regression equation is Y 14.4 8.69 X1 + 13.52 X2 Predictor Constant X1 X2 Coef 14.448 SE Coef 8.191 1.555 2.085 1.76 13.517 Analysis of Variance DE 2 SOURCE Regression Residual Error Total MS 720.0