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
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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](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F1727b38e-50df-47e0-90fa-89241e970545%2F508d0321-d302-4684-b840-1998e84e92a2%2Fj6e3q2tq_processed.jpeg&w=3840&q=75)
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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