Answer Happy

2. [-/2.77 Points] DETAILS ASWSBE14 14.E.015. Consider the data. 1 2 3 4 5 5 vi 4 8 6 10 12 The estimated regression equation for these data is ý = 2.60 + 1.80x. (a) Compute SSE, SST, and SSR using equations SSE = [(y; - Ý)2, SST = Ily; -72, and SSR = 3(,- )2 SSE = SST = SSR = (b) Compute the coefficient of determination r2. 2 = 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 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 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.)