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

Extracted text: Consider the data. 3. 12 14 55 35 60 10 25 The estimated regression equation for these data is ŷ = 70 – 3x. (a) Compute SSE, SST, and SSR using equations SSE = E(y; - ŷ;)?, sST = E(y; - y)?, and SSR = SSE = 110 SST = SSR = 170 (b) Compute the coefficient of determination r. (Round your answer to three decimal places.) = .930 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.) .965 20