5. [-/18 Points] Consider the data. DETAILS MY NOTES ASWSBE15 14.E.015. x; 1 2345 Yi 3 7 4 10 12 The estimated regression equation for these data is = 0.90 + 2.10x. (a) Compute SSE, SST, and SSR using equations SSE = [(y; ;), SST = (y; y), and SSR = - (; - )2. SSE = SST = SSR = (b) Compute the coefficient of determination r. 12 = 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 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 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.) ASK YOUR TEACHER PRACTICE ANOTHER