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ted regression equation for these data is ŷ= 66.18-2.38x, e SSE, SST, and SSR. (to 2 decimals) (to 2 decimals) (to 2 decimals) e the coefficient of determination ². Comment on the goodness of fit. (to 3 decimals)

ted regression equation for these data is ŷ= 66.18-2.38x, e SSE, SST, and SSR. (to 2 decimals) (to 2 decimals) (to 2 decimals) e the coefficient of determination ². Comment on the goodness of fit. (to 3 decimals)

Calculus For The Life Sciences
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 8E
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Given are five observations for two variables, x and y. The estimated regression equation for these data is ŷ = 66.18 - 2.38x. a. Compute SSE, SST, and SSR. 2 9 14 18 20 Xi Yi 50 60 41 18 12 SSE (to 2 decimals) SST (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination r². Comment on the goodness of fit. (to 3 decimals) fit; The least squares line provided an good c. Compute the sample correlation coefficient. Enter negative value as negative number. (to 3 decimals) *% of the variability in y has been explained by the estimated regression equation (to 1 decimal).
Transcribed Image Text:Given are five observations for two variables, x and y. The estimated regression equation for these data is ŷ = 66.18 - 2.38x. a. Compute SSE, SST, and SSR. 2 9 14 18 20 Xi Yi 50 60 41 18 12 SSE (to 2 decimals) SST (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination r². Comment on the goodness of fit. (to 3 decimals) fit; The least squares line provided an good c. Compute the sample correlation coefficient. Enter negative value as negative number. (to 3 decimals) *% of the variability in y has been explained by the estimated regression equation (to 1 decimal).
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