Consider the data.

x_i

3 12 6 20 14

y_i

55 35 45 10 15

The estimated regression equation for these data is = 62.25 2.75x.

(a)

Compute SSE, SST, and SSR using equations SSE = (y_{i i})²,

SST = (y_i y)²,

and SSR = (_i 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 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 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.

(c)

Compute the sample correlation coefficient. (Round your answer to three decimal places.)

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