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A sales manager collected the following data on years of experience andy - annual sales ($1.000s). The estimated regression equation for these data is 9-1

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A sales manager collected the following data on years of experience andy - annual sales ($1.000s). The estimated regression equation for these data is 9-1 + 4 Salesperson Year Experience Annual Sales ($1,000) 1 1 30 3 97 97 4 4 102 6 103 6 7 10 10 128 117 10 13 136 (a) Compute SST. 5, and SSE IST - 2542 X SSR - 2212 SSE - 130 X (6) Compute the coeficient of determination round your answer to the decimal places.) 2015 Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) O 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 last squares line. O The least squares line did not provide a good fit as a small proportion of the variability iny 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 X (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.) A sales manager collected the following data on years of experience andy - annual sales ($1.000s). The estimated regression equation for these data is 9-1 + 4 Salesperson Year Experience Annual Sales ($1,000) 1 1 30 3 97 97 4 4 102 6 103 6 7 10 10 128 117 10 13 136 (a) Compute SST. 5, and SSE IST - 2542 X SSR - 2212 SSE - 130 X (6) Compute the coeficient of determination round your answer to the decimal places.) 2015 Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) O 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 last squares line. O The least squares line did not provide a good fit as a small proportion of the variability iny 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 X (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)

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