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Test interviews of two personnel evaluation techniques are available, the first requires a two-hour test interview while the second can be completed in less than an hour. The table below is the output of the regression analysis of the 15 individuals who took both tests: (i) Calculate the sample correlation coefficient between Test 1 and Test 2 (ii) if the correlation of determination between test 1 and test 2 is M. Comment on the value of this correlation determination.

Test interviews of two personnel evaluation techniques are available, the first requires a two-hour test interview while the second can be completed in less than an hour. The table below is the output of the regression analysis of the 15 individuals who took both tests: (i) Calculate the sample correlation coefficient between Test 1 and Test 2 (ii) if the correlation of determination between test 1 and test 2 is M. Comment on the value of this correlation determination.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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Test interviews of two personnel evaluation techniques are available, the first requires a two-hour test interview while the second can be completed in less than an hour. The table below is the output of the regression analysis of the 15 individuals who took both tests:

(i) Calculate the sample correlation coefficient between Test 1 and Test 2

(ii) if the correlation of determination between test 1 and test 2 is M. Comment on the value of this correlation determination.

 

Regression Statistics Multiple R 0.953935025 R Square Adjusted R Square 0.903068342 Standard Error 3.134808415 Observations 15 ANOVA Significance df SS MS F F Regression 1 1291.582 1291.582 131.4316573 3.60668E-08 Residual 13 127.7513 9.827024 Total 14 1419.333 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept 11.66533278 5.295713 -2.20279 0.046260025 -23.1060256 -0.224639973 Test 1 (X) 0.755016772 0.065858 J 3.60668E-08 IN
Transcribed Image Text:Regression Statistics Multiple R 0.953935025 R Square Adjusted R Square 0.903068342 Standard Error 3.134808415 Observations 15 ANOVA Significance df SS MS F F Regression 1 1291.582 1291.582 131.4316573 3.60668E-08 Residual 13 127.7513 9.827024 Total 14 1419.333 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept 11.66533278 5.295713 -2.20279 0.046260025 -23.1060256 -0.224639973 Test 1 (X) 0.755016772 0.065858 J 3.60668E-08 IN
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