Given are five observations for two variables, and y. I SSE SST 2 7 10 12 14 60 59 46 16 12 Y/₁ The estimated regression equation for these data is = 77.87-4.36z. a. Compute SSE, SST, and SSR.. (to 2 decimals) (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination 2. Comment on the goodness of fit. (to 3 decimals) The least squares line provided an - Select your answer - fit; estimated regression equation (to 1 decimal). 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
Given are five observations for two variables, and y. I SSE SST 2 7 10 12 14 60 59 46 16 12 Y/₁ The estimated regression equation for these data is = 77.87-4.36z. a. Compute SSE, SST, and SSR.. (to 2 decimals) (to 2 decimals) SSR (to 2 decimals) b. Compute the coefficient of determination 2. Comment on the goodness of fit. (to 3 decimals) The least squares line provided an - Select your answer - fit; estimated regression equation (to 1 decimal). 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
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 6PPS
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Transcribed Image Text:Given are five observations for two variables, and y.
X
2 7 10 12 14
60 59 46 16 12
Yi
The estimated regression equation for these data is = 77.87-4.36x.
a. Compute SSE, SST, and SSR..
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)
The least squares line provided an Select your answer fit;
estimated regression equation (to 1 decimal).
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
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