Consider the data.

x_i 1 2 3 4 5

y_i 3 7 5 11 14

The estimated regression equation for these data is=0.20+2.60x.

(a)

Compute SSE, SST, and SSR using equationsSSE =(y_ii)²,

SST =(y_iy)²,

andSSR =(_iy)².

SSE=

SST=

SSR=

(b)

Compute the coefficient of determinationr².

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 large proportion of the variability inyhas been explained by the least squares line.
• The least squares line provided a good fit as a large proportion of the variability inyhas been explained by the least squares line.
• The least squares line did not provide a good fit as a small proportion of the variability inyhas been explained by the least squares line.
• The least squares line provided a good fit as a small proportion of the variability inyhas been explained by the least squares line.

(c)

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