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DATAfile: Sales 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 ý = 80 Years of Annual Sales Salesperson Experience ($1,000s) 1 80 2 3 97 3 4 92 4 4 102 103 6 111 7 10 119 8 10 123 9 11 117 10 13 136 (a) Compute SST, SSR, and SSE. SST = 2502 X SSR = 2272 SSE = 230 X (b) Compute the coefficient of determination r. (Round your answer to three decimal places.) ,2= 908 x 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 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 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. (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.) .953X

DATAfile: Sales 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 ý = 80 Years of Annual Sales Salesperson Experience ($1,000s) 1 80 2 3 97 3 4 92 4 4 102 103 6 111 7 10 119 8 10 123 9 11 117 10 13 136 (a) Compute SST, SSR, and SSE. SST = 2502 X SSR = 2272 SSE = 230 X (b) Compute the coefficient of determination r. (Round your answer to three decimal places.) ,2= 908 x 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 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 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. (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.) .953X

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
6th Edition
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Bruce Crauder, Benny Evans, Alan Noell
Chapter3: Straight Lines And Linear Functions
Section3.CR: Chapter Review Exercises
Problem 15CR: Life Expectancy The following table shows the average life expectancy, in years, of a child born in...
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DATAfile: Sales 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. Years of Annual Sales Salesperson Experience ($1,000s) 1 80 2 3 97 3 4 92 4 4 102 103 6 111 7 10 119 8 10 123 9 11 117 10 13 136 (a) Compute SST, SSR, and SSE. SST = 2502 X SSR = 2272 SSE = 230 X (b) Compute the coefficient of determination r. (Round your answer to three decimal places.) ,2= 908 x 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 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 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. (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.) .953X
Transcribed Image Text:DATAfile: Sales 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. Years of Annual Sales Salesperson Experience ($1,000s) 1 80 2 3 97 3 4 92 4 4 102 103 6 111 7 10 119 8 10 123 9 11 117 10 13 136 (a) Compute SST, SSR, and SSE. SST = 2502 X SSR = 2272 SSE = 230 X (b) Compute the coefficient of determination r. (Round your answer to three decimal places.) ,2= 908 x 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 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 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. (c) What is the value of the sample correlation coefficient? (Round your answer to three decimal places.) .953X
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