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 92 4 4 107 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 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 least squares line.     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. (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)

MATLAB: An Introduction with Applications
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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 of
Experience
Annual Sales
($1,000s)
1 1 80
2 3 97
3 4 92
4 4 107
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 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 least squares line.     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.
(c)
What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)
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