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: a.Using the method of least squares, the estimated regression will be? b.Suppose you must test the hypothesis at 5% significance level that versus using t-test. The value of J will be?
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: a.Using the method of least squares, the estimated regression will be? b.Suppose you must test the hypothesis at 5% significance level that versus using t-test. The value of J will be?
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
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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
a.Using the method of least squares, the estimated regression will be?
b.Suppose you must test the hypothesis at 5% significance level that versus using t-test. The value of J will be?
![Regression Statistics
Multiple R
0.953935025
R Square
M
Adjusted R Square 0.903068342
Standard Error
3.134808415
Observations
15
ANOVA
df
ss
MS
F
Significance F
1291.582
1291.582 131.4316573 3.60668E-08
Regression
Residual
13
127.7513
9.827024
Total
14
1419.333
Coefficients
Standard Error
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
3.60668E-08 N](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F7eea6dc0-72ac-4bb4-af82-e9b744ff9a04%2Fac179a20-dd42-4ed4-b794-a4a9c2ff6f60%2F3bgbft9_processed.png&w=3840&q=75)
Transcribed Image Text:Regression Statistics
Multiple R
0.953935025
R Square
M
Adjusted R Square 0.903068342
Standard Error
3.134808415
Observations
15
ANOVA
df
ss
MS
F
Significance F
1291.582
1291.582 131.4316573 3.60668E-08
Regression
Residual
13
127.7513
9.827024
Total
14
1419.333
Coefficients
Standard Error
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
3.60668E-08 N
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