The following estimated regression equation based on 10 observations was presented. ý = 29.1270 + 0.5106Xq + 0.4980X, The values of SST and SSR are 6,714.125 and 6,225.375, respectively. (a) Find SSE. SSE= 488.75 (b) Compute R2. (Round your answer to three decimal places.) R² = 0.927 (c) Compute R₂². (Round your answer to three decimal places.) R₁₂²= 0.906 (d) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) O The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. O The estimated regression equation did not provide a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. O The estimated regression equation did not provide a good fit as a large proportion of the variability in y has been explained by the estimated regression equation. O The estimated regression equation provided a good fit as a large proportion of the variability in v has been explained by the estimated regression equation.
The following estimated regression equation based on 10 observations was presented. ý = 29.1270 + 0.5106Xq + 0.4980X, The values of SST and SSR are 6,714.125 and 6,225.375, respectively. (a) Find SSE. SSE= 488.75 (b) Compute R2. (Round your answer to three decimal places.) R² = 0.927 (c) Compute R₂². (Round your answer to three decimal places.) R₁₂²= 0.906 (d) Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) O The estimated regression equation provided a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. O The estimated regression equation did not provide a good fit as a small proportion of the variability in y has been explained by the estimated regression equation. O The estimated regression equation did not provide a good fit as a large proportion of the variability in y has been explained by the estimated regression equation. O The estimated regression equation provided a good fit as a large proportion of the variability in v has been explained by the estimated regression equation.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![The following estimated regression equation based on 10 observations was presented:
\[
\hat{y} = 29.1270 + 0.5106x_1 + 0.4980x_2
\]
The values of SST and SSR are 6,714.125 and 6,225.375, respectively.
(a) **Find SSE.**
- **SSE** = 488.75
(b) **Compute \( R^2 \).** (Round your answer to three decimal places.)
\[
R^2 = 0.927
\]
(c) **Compute \( R^2_a \).** (Round your answer to three decimal places.)
\[
R^2_a = 0.906
\]
(d) **Comment on the goodness of fit.** (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
- The estimated regression equation provided a good fit as a large proportion of the variability in \( y \) has been explained by the estimated regression equation.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ff7b76bbb-1122-4c75-9c9e-2038b7c47d4e%2F5c52019c-9251-41cd-89b8-f7b5505b73a2%2Fd83rqkc_processed.png&w=3840&q=75)
Transcribed Image Text:The following estimated regression equation based on 10 observations was presented:
\[
\hat{y} = 29.1270 + 0.5106x_1 + 0.4980x_2
\]
The values of SST and SSR are 6,714.125 and 6,225.375, respectively.
(a) **Find SSE.**
- **SSE** = 488.75
(b) **Compute \( R^2 \).** (Round your answer to three decimal places.)
\[
R^2 = 0.927
\]
(c) **Compute \( R^2_a \).** (Round your answer to three decimal places.)
\[
R^2_a = 0.906
\]
(d) **Comment on the goodness of fit.** (For purposes of this exercise, consider a proportion large if it is at least 0.55.)
- The estimated regression equation provided a good fit as a large proportion of the variability in \( y \) has been explained by the estimated regression equation.
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