Consider the data. X; 3 5 4 8 6 10 12 The estimated regression equation for these data is ý = 2.60 + 1.80x. (a) Compute SS, ST, and SSR using equations SSE = E(y, - ý)?, SST = {(y, - 7)?, and sR =...

Extracted text: Consider the data. X; 3 5 4 8 6 10 12 The estimated regression equation for these data is ý = 2.60 + 1.80x. (a) Compute SS, ST, and SSR using equations SSE = E(y, - ý)?, SST = {(y, - 7)?, and sR = E(9, - y)?. SSE = SST = SSR = (b) Compute the coefficient of determination r2. 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 large 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 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.)