Consider the data.X;3 12 6 20 14604050 15 20The estimated regression equation for these data is ý = 67.25 -2.75x.(a) Compute SSE, SST, and SSR using equations SSE = (y₁ - ;)², SST = (y₁ - y)², and SSR = [(y₁ - y)².SSE = 1361.25XSST =SSR =(b) Compute the coefficient of determination 2. (Round your answer to three decimal places.)² = 0.920Comment 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 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 did not provide a good fit as a large proportion of the variability in y has been explained by the least squaresline.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.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 squaresline.(c) Compute the sample correlation coefficient. (Round your answer to three decimal places.)X

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Consider the data. x 3 12 6 20 14 Y; 60 40 50 15 20 The estimated regression equation for these data is ý = 67.25 -2.75x. (a) Compute SSE, SST, and SSR using equations SSE = (x,-)², SST = (y₁ - y)², and SSR = = (₁-7)². x SSE=1361.25 SST = SSR =

Consider the data. x 3 12 6 20 14 Y; 60 40 50 15 20 The estimated regression equation for these data is ý = 67.25 -2.75x. (a) Compute SSE, SST, and SSR using equations SSE = (x,-)², SST = (y₁ - y)², and SSR = = (₁-7)². x SSE=1361.25 SST = SSR =

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

Chapter3: Straight Lines And Linear Functions

Section3.CR: Chapter Review Exercises

Problem 15CR: Life Expectancy The following table shows the average life expectancy, in years, of a child born in...

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Question

100%

Consider the data.
X;
3 12 6 20 14
60
40
50 15 20
The estimated regression equation for these data is ý = 67.25 -2.75x.
(a) Compute SSE, SST, and SSR using equations SSE = (y₁ - ;)², SST = (y₁ - y)², and SSR = [(y₁ - y)².
SSE = 1361.25
X
SST =
SSR =
(b) Compute the coefficient of determination 2. (Round your answer to three decimal places.)
² = 0.920
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 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 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 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 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.)
X

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