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    Multiple regression

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    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.

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    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.

    $2.49

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