# Multiple regression

Recall that in Exercise 45 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 minus 8.69 x1 minus 13.5 x2

Where

X1 = length of service in years

X2 = wage rate in dollars

Y= job satisfaction test score (higher scores indicate greater job satisfaction)

A portion of the Minitab computer output follows.

Predictor Coef StDev t-ratio

Constant 14.448 8.191 1.76

X1 1.555

X2 13.517 2.085

S = 3.773 R-sq ______% R-sq (adj) = __%

Analysis of Variance

Source DF SS MS F

Regression 2 ____ ____ ____

Error ____ 71.17 _____ ____

Total 7 720.0

a. Complete the missing entries in this output.

b. Compute F test using level of significance = .05 to see whether a significant relationship is present.

c. Did the estimated regression equation provide a good fit to the data on employees Explain.

d Use the t test and level of signficance =.05 to test H0: b1 = 0.

https://brainmass.com/statistics/regression-analysis/multiple-regression-output-entries-6150

#### Solution Summary

Completes the missing entries of a multiple regression output. Uses F and t tests to see whether a significant relationship is present.