Given are five observations for two variables, x and y. 15 14 16 19 Yi 56 55 48 17 13 The estimated regression equation for these data is ŷ = 63.98 –- 2.38a. a. Compute SSE, SST, and SSR. SSE (to 2 decimals) SST (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination p2. Comment on the goodness of fit. (to 3 decimals) The least squares line provided an Select your answer - fit; % of the variability in y has been explained by the estimated regression equation (to 1 decimal). c. Compute the sample correlation coefficient. Enter negative value as negative number. (to 3 decimals)

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
6th Edition
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Bruce Crauder, Benny Evans, Alan Noell
Chapter5: A Survey Of Other Common Functions
Section5.6: Higher-degree Polynomials And Rational Functions
Problem 1TU: The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t=...
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Given are five observations for two variables, a and y.
1
5 14 16 19
56 55 48 17 13
The estimated regression equation for these data is ŷ = 63.98 – 2.38x.
a. Compute SSE, SST, and SSR,
SSE
(to 2 decimals)
SST
(to 2 decimals)
SSR
(to 2 decimals)
b. Compute the coefficient of determination p2. Comment on the goodness of fit.
(to 3 decimals)
The least squares line provided an - Select your answer - v fit;
% of the variability in y has been explained by the estimated regression equation (to 1 decimal).
c. Compute the sample correlation coefficient. Enter negative value as negative number.
(to 3 decimals)
Transcribed Image Text:Given are five observations for two variables, a and y. 1 5 14 16 19 56 55 48 17 13 The estimated regression equation for these data is ŷ = 63.98 – 2.38x. a. Compute SSE, SST, and SSR, SSE (to 2 decimals) SST (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination p2. Comment on the goodness of fit. (to 3 decimals) The least squares line provided an - Select your answer - v fit; % of the variability in y has been explained by the estimated regression equation (to 1 decimal). c. Compute the sample correlation coefficient. Enter negative value as negative number. (to 3 decimals)
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