# decision rule/test statistic

The production manager of High Point Sofa and Chair, a large furniture manufacturer located in North Carolina, is studying the job performance ratings of a sample of15 electrical repairmen employed by the company. An aptitude test is required by the human resources department to become an electrical repairman. The productionmanager was able to get the score for each repairman in the sample. In addition, he determined which of the repairmen were union members (code = 1) and which were not(code = 0). The sample information is reported below and the multiple regression equation using the job performance score as the dependent variable and aptitude testscore and union membership as independent variables is given as Performance = 29.276 + 5.223 Aptitude + 22.135 Union. Test for autocorrelation at the .05 significancelevel.
Worker Job
Performance
Score Aptitude Test Score Union Membership
Abbott 58 5 0
Anderson 53 4 0
Bender 33 10 0
Bush 97 10 0
Center 36 2 0
Coombs 83 7 0
Eckstine 67 6 0
Gloss 84 9 0
Herd 98 9 1
Householder 45 2 1
Iori 97 8 1
Lindstrom 90 6 1
Mason 96 7 1
Pierse 66 3 1
Rohde 82 6 1
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(a) State the decision rule for .05 significance level: H0: ? = 0; H1: ? > 0 (Round your answer to 2 decimal places.)

Reject H0 if d <

Do not reject H0 if d>

Neither rejected nor not rejected H0 if = d =

(b-1) Compute the value of the test statistic. (Round your answer to 2 decimal places.)

Value of the test statistic

(b-2) Is there any autocorrelation between the residuals? Use the .05 significance level.

H0. There autocorrelation
between the residuals.