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## Statistics

Significant test for slope

The personnel director from 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 + 13.52x2

Where
x1 = length of service (years)
x2 = wage rate (dollars)
y = job satisfaction test score (higher score indicate greater job satisfaction)

A portion of the Minitab computer output follows. The regression equation is
Y = 14.4 - 8.69 X1 + 13.52 X2

 Predictor Coef SE Coef T 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 Residual Error 71.17 Total 7 720.0

a. Complete the missing entries in this output (to 2 decimals).
Estimated Regression Equation

 Predictor Coefficient SE Coefficient T Constant 14.448 8.191 1.76 X1 1.555 X2 13.517 2.085

R2_____ %
Analysis of Variance

 Source DF SS MS F Regression 2 324.415 22.79 Residual Error 5 71.17 14.234 Total 7 720.0

b. Using α = .05, is a significant relationship present?

c. Did estimated regression equation provide a good fit to the data?

d. Using the t test and α = .05 to test H0: β1 = 0 and β2 = 0
Compute the t test statistic for β1 (to 2 decimals).
What is the conclusion?
figure the t test statistic for β2 (to 2 decimals).
What is the conclusion?

Statistics and Probability, Statistics

• Category:- Statistics and Probability
• Reference No.:- M922830

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