effectiveness of ambient noise reduction. 5 cores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is p=22.591973+0.324080x ; ​
where x e price (\$) and y= overall score. (a) Compute 5ST, SSR, and 5SE, (Round your answers to three decimal places.) SST = SSR = SSE = ​
(b) Compute the coetficient of determination r 2
. (Round your answer to three decimal places.) r 2
= Comment on the goodness of fit. (For purposes of this exercise, consider a propsrion large it it is at least 0.55.) The leact squares line provided a good fit as a small peoportion of the variability in y has been explained by the least squares line. The least squares fine did not previde a good fat as a targe proportion of the variability in y has been explained by the least squaree line: The inat couares lne provided a good fit as a tarce proportion of the variabily in y has been explained by the least squares line. (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST =
SSR =
SSE = ​
(b) Compute the coefficient of determination r 2
. (Round your answer to three decimal places.) r 2
= 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 fine. The least squaros 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, 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) What is the value of the sample correlation coetficient? (Round your answer to three decimal places.)