Essentials of Modern Business Statistics with Microsoft Office Excel (Book Only)
7th Edition
ISBN: 9781337298353
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams
Publisher: South-Western College Pub
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Chapter 15.3, Problem 13E
a)
To determine
To find: The value of
b)
To determine
To find: The value of
c)
To determine
To comment: On the goodness of the fit of the data.
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The following estimated regression equation based on 30 observations was presented.
ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4
The values of SST and SSR are 1,808 and 1,780, respectively.
(a)
Compute R2.
(b)
Compute
Ra2.
(c)
Comment on the goodness of fit.
The following estimated regression equation is based on 30 observations.
ŷ = 18.3 + 3.9x1 − 2.2x2 + 7.5x3 + 2.5x4
The values of SST and SSR are 1,805 and 1,762, respectively.
a. Compute R2 = (to 3 decimals).
b. Compute Ra2 = (to 3 decimals).
The following estimated regression equation based on 10 observations was presented.
ŷ = 29.1260 + 0.5306x1 + 0.4680x2
The values of SST and SSR are 6,728.125 and 6,215.375, respectively.
(a)
Find SSE.
SSE =
(b)
Compute R2. (Round your answer to three decimal places.)
R2 =
(c)
Compute
Ra2.
(Round your answer to three decimal places.)
Ra2 =
(d)
Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation.The estimated regression equation did not provide a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. The estimated regression equation provided a good fit as a large proportion of the variability in y has been explained by the estimated regression equation.
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Essentials of Modern Business Statistics with Microsoft Office Excel (Book Only)
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