Statistics for Business & Economics, Revised (MindTap Course List)
12th Edition
ISBN: 9781285846323
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: South-Western College Pub
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Textbook Question
Chapter 14.3, Problem 19E
In exercise 7 a sales manager collected the following data on x = annual sales and y = years of experience. The estimated regression equation for these data is ŷ = 80 + 4x.
| Salesperson | Years of Experience | Annual Sales ($1000s) |
| 1 | 1 | 80 |
| 2 | 3 | 97 |
| 3 | 4 | 92 |
| 4 | 4 | 102 |
| 5 | 6 | 103 |
| 6 | 8 | 111 |
| 7 | 10 | 119 |
| 8 | 10 | 123 |
| 9 | 11 | 117 |
| 10 | 13 | 136 |
- a. Compute SST, SSR, and SSE.
- b. Compute the coefficient of determination r2. Comment on the goodness of fit.
- c. What is the value of the sample
correlation coefficient ?
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Students have asked these similar questions
A sales manager collected the following data on x = years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is
ŷ = 80 + 4x.
Salesperson
Years ofExperience
Annual Sales($1,000s)
1
1
80
2
3
97
3
4
97
4
4
102
5
6
103
6
8
101
7
10
119
8
10
118
9
11
127
10
13
136
(a)
Compute SST, SSR, and SSE.
SST = SSR = SSE =
(b)
Compute the coefficient of determination
r2.
(Round your answer to three decimal places.)
r2
=
Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line. The least squares line did not provide a good fit as a small proportion of the variability in y has been explained by the least squares line. The least squares line provided a good fit as a large proportion of the variability in y has been explained by the…
A sales manager collected the following data on x = years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is
ŷ = 80 + 4x.
Salesperson
Years ofExperience
Annual Sales($1,000s)
1
1
80
2
3
97
3
4
92
4
4
102
5
6
103
6
8
111
7
10
119
8
10
123
9
11
117
10
13
136
(a)
Compute SST, SSR, and SSE.
SST=SSR=SSE=
(b)
Compute the coefficient of determination
r2.
(Round your answer to three decimal places.)
r2
=
Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line.The least squares line provided a good fit as a large proportion of the variability in y has been explained by the least squares line. The least squares line did not provide a good fit as a large proportion of the variability in y has been explained by the…
A sales manager collected the following data on x = years of experience and y = annual sales ($1,000s). The estimated regression equation for these data is
ŷ = 81 + 4x.
Salesperson
Years ofExperience
Annual Sales($1,000s)
1
1
80
2
3
97
3
4
97
4
4
102
5
6
103
6
8
111
7
10
119
8
10
128
9
11
117
10
13
136
(a)
Compute SST, SSR, and SSE.
SST=
SSR=
SSE=
(b)
Compute the coefficient of determination
r2.
(Round your answer to three decimal places.)
r2
=
Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line.The least squares line did not provide a good fit as a small proportion of the variability in y has been explained by the least squares line. The least squares line provided a good fit as a large proportion of the variability in y has been explained by the…
Chapter 14 Solutions
Statistics for Business & Economics, Revised (MindTap Course List)
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