Basic Business Statistics, Student Value Edition
14th Edition
ISBN: 9780134685113
Author: Mark L. Berenson, David M. Levine, David F. Stephan, Kathryn Szabat
Publisher: PEARSON
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Chapter 16, Problem 37PS
a.
To determine
Perform a residual analysis.
b.
To determine
Compute
c.
To determine
Compute the MAD.
d.
To determine
Discuss which forecasting model should be selected.
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) In estimating the regression in problem #2, you are also concerned that the t-statistics may be inflated because of the presence of conditional heteroscedasticity. You conduct a regression of the squared residuals against the dummy variables X1, X2, and X3 and find that for the squared residuals regression:
Multiple R
0.4145
R Square
0.1718
Adjusted R Square
0.1600
SEE
92.3760
Conduct a test at the level to see if conditional heteroskedasticity is present
In view of your answer for a), what needs to be done?
In estimating the regression in problem #2, you are also concerned that the t-statistics may be inflated because of the presence of conditional heteroscedasticity. You conduct a regression of the squared residuals against the dummy variables X1, X2, and X3 and find that for the squared residuals regression:
Multiple R
0.4145
R Square
0.1718
Adjusted R Square
0.1600
SEE
92.3760
Conduct a test at the level to see if conditional heteroskedasticity is present
) In estimating the regression in problem #2, you are also concerned that the t-statistics may be inflated because of the presence of conditional heteroscedasticity. You conduct a regression of the squared residuals against the dummy variables X1, X2, and X3 and find that for the squared residuals regression:
Multiple R
0.4145
R Square
0.1718
Adjusted R Square
0.1600
SEE
92.3760
Conduct a test at the level to see if conditional heteroskedasticity is present and from your results, what needs to be done?
Chapter 16 Solutions
Basic Business Statistics, Student Value Edition
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