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Consider the data. xi 1 2 3 4 5 Yi 4 85 11 12 The estimated regression equation for these data is ŷ = 2.30 + 1.90x. (a) Compute SSE, SST, and SSR using equations SSE (y,-9)2, SST (y, v)2, and SSR (9,-y)². SSE= SST= SSR= = - (b) Compute the coefficient of determination ². 12² = 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 provided a good fit as a small proportion of the variability in y has been explained by the least squares line. O 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. 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 large proportion of the variability in y has been explained by the least squares line. (c) Compute the sample correlation coefficient. (Round your answer to three decimal places.)

Consider the data. xi 1 2 3 4 5 Yi 4 85 11 12 The estimated regression equation for these data is ŷ = 2.30 + 1.90x. (a) Compute SSE, SST, and SSR using equations SSE (y,-9)2, SST (y, v)2, and SSR (9,-y)². SSE= SST= SSR= = - (b) Compute the coefficient of determination ². 12² = 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 provided a good fit as a small proportion of the variability in y has been explained by the least squares line. O 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. 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 large proportion of the variability in y has been explained by the least squares line. (c) Compute the sample correlation coefficient. (Round your answer to three decimal places.)

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Consider the data. xi 1 2 3 4 5 Yi 4 85 11 12 The estimated regression equation for these data is ŷ = 2.30 + 1.90x. (a) Compute SSE, SST, and SSR using equations SSE (y,-9)2, SST (y, v)2, and SSR (9,-y)². SSE= SST= SSR= = - (b) Compute the coefficient of determination ². 12² = 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 provided a good fit as a small proportion of the variability in y has been explained by the least squares line. O 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. 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 large proportion of the variability in y has been explained by the least squares line. (c) Compute the sample correlation coefficient. (Round your answer to three decimal places.)
Transcribed Image Text:Consider the data. xi 1 2 3 4 5 Yi 4 85 11 12 The estimated regression equation for these data is ŷ = 2.30 + 1.90x. (a) Compute SSE, SST, and SSR using equations SSE (y,-9)2, SST (y, v)2, and SSR (9,-y)². SSE= SST= SSR= = - (b) Compute the coefficient of determination ². 12² = 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 provided a good fit as a small proportion of the variability in y has been explained by the least squares line. O 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. 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 large proportion of the variability in y has been explained by the least squares line. (c) Compute the sample correlation coefficient. (Round your answer to three decimal places.)
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