Consider the data. 2 5 12 15 The estimated regression equation for these data is y = 1.20 + 2.60x. (a) Compute SSE, SST, and SSR using equations SSE = >(y, - y,) , SST = >(y, - y)?, and SSR = >(), - y)2. 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.) 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. 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. 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. (c) Compute the sample correlation coefficient. (Round your answer to three decimal places.) Submit