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MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Please answer all subparts with explanation.
![Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is
0.860 and the least squares regression line is y=0 209x+11.647. Complete parts (a) and (b) below.
Height, x
27 25.5 26.5 25 25 27.75 26.75 26 26 75 27.25 27 25 27 D
Head Circumference, y 172 16.9 17.1 17.0 17.5 171 171 174 173 173 174
(a) Compute the coefficient of determination, R
R²=% (Round to one decimal place as needed.)
(b) Interpret the coefficient of determination and comment on the adequacy of the linear model
Approximately % of the variation in
residual plot, the linear model appears to be
is explained by the least squares regression model. According to the](https://content.bartleby.com/qna-images/question/1727b38e-50df-47e0-90fa-89241e970545/508d0321-d302-4684-b840-1998e84e92a2/j6e3q2tq_thumbnail.jpeg)
Transcribed Image Text:Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is
0.860 and the least squares regression line is y=0 209x+11.647. Complete parts (a) and (b) below.
Height, x
27 25.5 26.5 25 25 27.75 26.75 26 26 75 27.25 27 25 27 D
Head Circumference, y 172 16.9 17.1 17.0 17.5 171 171 174 173 173 174
(a) Compute the coefficient of determination, R
R²=% (Round to one decimal place as needed.)
(b) Interpret the coefficient of determination and comment on the adequacy of the linear model
Approximately % of the variation in
residual plot, the linear model appears to be
is explained by the least squares regression model. According to the
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