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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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