Consider the data. xi 1 2 3 4 5 yi 4 8 4 12 12 The estimated regression equation for these data is ŷ = 2.00 + 2.00x. (a) Compute SSE, SST, and SSR using equations SSE = Σ(yi − ŷi)2, SST = Σ(yi − y)2, and SSR = Σ(ŷi − y)2. SSE=? SST=? SSR=? (b) Compute the coefficient of determination r2. r2 = ?? 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 did not provide a good fit as a small 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 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 provided a good fit as a small proportion of the variability in y has been explained by the least squares line. (c)Compute the sample correlation coefficient. (Round your answer to three decimal places.) ??
Consider the data. xi 1 2 3 4 5 yi 4 8 4 12 12 The estimated regression equation for these data is ŷ = 2.00 + 2.00x. (a) Compute SSE, SST, and SSR using equations SSE = Σ(yi − ŷi)2, SST = Σ(yi − y)2, and SSR = Σ(ŷi − y)2. SSE=? SST=? SSR=? (b) Compute the coefficient of determination r2. r2 = ?? 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 did not provide a good fit as a small 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 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 provided a good fit as a small proportion of the variability in y has been explained by the least squares line. (c)Compute the sample correlation coefficient. (Round your answer to three decimal places.) ??
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Consider the data.
|
xi
|
1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|
|
yi
|
4 | 8 | 4 | 12 | 12 |
The estimated regression equation for these data is
ŷ = 2.00 + 2.00x.
(a)
Compute SSE, SST, and SSR using equations
SSE = Σ(yi − ŷi)2, SST = Σ(yi − y)2, and SSR = Σ(ŷi − y)2.
SSE=?
SST=?
SSR=?
(b)
Compute the coefficient of determination r2.
r2 = ??
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 did not provide a good fit as a small 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 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 provided a good fit as a small proportion of the variability in y has been explained by the least squares line.
(c)Compute the sample correlation coefficient . (Round your answer to three decimal places.)
??
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