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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 A Height, x 27 25.5 26.5 25 25 27 75 26 75 Head Circumference, y 172 169 17.1 17.0 17.5 17.1 (a) Compute the coefficient of determination, R R²=% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment Approximately of the variation in residual plot, the linear model appears to be 26 26 75 27 25 27 25 27 17.1 174 173 173 174 on the adequacy of the linear model is explained by the least squares regression model. According to the

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 A Height, x 27 25.5 26.5 25 25 27 75 26 75 Head Circumference, y 172 169 17.1 17.0 17.5 17.1 (a) Compute the coefficient of determination, R R²=% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination and comment Approximately of the variation in residual plot, the linear model appears to be 26 26 75 27 25 27 25 27 17.1 174 173 173 174 on the adequacy of the linear model is explained by the least squares regression model. According to the

MATLAB: An Introduction with Applications
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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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
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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