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 of Experience Annual Sales ($1,000s) 1 1 80 2 3 97 3 4 92 4 4 107 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 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 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. (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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Author:Amos Gilat
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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 = 80 + 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 8 101
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 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 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.
(c)
What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)
 
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