Consider the data. 1 2 3 4 5 Y 4 B 4 12 12 The estimated regression equation for these data is 9 2.00 +2.00x. (a) Compute SSE, SST, and SSR using equations SSE-ty, -9), SST (y,-), and SSR (9,-) SSE-> SST-> SSR- (b) Compute the coefficient of determination . 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.)