Consider the data.
The estimated regression equation for these data is
ŷ = 75.75 − 3.25x.
(a)
Compute SSE, SST, and SSR using equations
SSE = Σ(yi −ŷi)2,
SST = Σ(yi −y)2,
and
SSR = Σ(ŷi −y)2.
SSE = SST = SSR =
(b)
Compute the coefficient of determination
r2.
(Round your answer to three decimal places.)
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 did not provide a good fit as a largeproportion of the variability in y has been explained bythe least squares line.The least squares line provided a good fitas a large proportion of the variability in y has beenexplained by the least squaresline.     The least squares line did notprovide a good fit as a small proportion of the variability iny has been explained by the least squares line.The leastsquares line provided a good fit as a small proportion of thevariability in y has been explained by the least squaresline.
(c)
Compute the sample correlation coefficient. (Round your answerto three decimal places.)
