Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.896 and the least squares regression line is y = 0.258x + 10.348. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.2 16.9 17.2 16.9 17.5 17.4 17.1 17.3 17.3 17.3 17.3 27 25.5 26.5 25.5 27.25 26.75 26 26.75 27.25 27.25 26.75 ..... (a) Compute the coefficient of determination, R2. R2 =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately % of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model.

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The options for part b are: head circumference or height

Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is
0.896 and the least squares regression line is y = 0.258x+ 10.348. Complete parts (a) and (b) below.
Height, x
Head Circumference, y 17.2 16.9 17.2 16.9 17.5
27
25.5 26.5 25.5 27.25 26.75 26 26.75 27.25 27.25 26.75
17.4
17.1
17.3 17.3
17.3 17.3
(a) Compute the coefficient of determination, R2.
R? =% (Round to one decimal place as needed.)
(b) Interpret the coefficient of determination.
Approximately% of the variation in
(Round to one decimal place as needed.)
is explained by the least-squares regression model.
Transcribed Image Text:Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.896 and the least squares regression line is y = 0.258x+ 10.348. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.2 16.9 17.2 16.9 17.5 27 25.5 26.5 25.5 27.25 26.75 26 26.75 27.25 27.25 26.75 17.4 17.1 17.3 17.3 17.3 17.3 (a) Compute the coefficient of determination, R2. R? =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately% of the variation in (Round to one decimal place as needed.) is explained by the least-squares regression model.
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