Consider the data. X; 3 12 20 14 Yi 55 35 60 10 25 The estimated regression equation for these data is ŷ = 70 – 3x. %D (a) Compute SSE, SST, and SSR using equations SSE = E(y; - ŷ;)², SST = E(y; -...

Extracted text: Consider the data. X; 3 12 20 14 Yi 55 35 60 10 25 The estimated regression equation for these data is ŷ = 70 – 3x. %D (a) Compute SSE, SST, and SSR using equations SSE = E(y; - ŷ;)², SST = E(y; - y)², and SSR = E(9; - 7)². SSE = SST = SSR = (b) Compute the coefficient of determination r. (Round your answer to three decimal places.) ,2 = %D 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 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. 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) Compute the sample correlation coefficient. (Round your answer to three decimal places.) Need Help? Read It