Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.883 and the least squares regression line is y = 0.134x+ 13.693. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 17.1 27.75 25.25 26 25.25 27.25 26.75 26 27.25 27 27.25 26.75 17.3 17.0 17.4 17.2 17.2 17.3 17.3 17.4 17.3 ..... (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 is explained by the least-squares regression model. (Round to one decimal place as needed.)

Big Ideas Math A Bridge To Success Algebra 1: Student Edition 2015
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ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
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Chapter4: Writing Linear Equations
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Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is
0.883 and the least squares regression line is y = 0.134x + 13.693. Complete parts (a) and (b) below.
Height, x
Head Circumference, y 17.4
27.75 25.25
26 25.25 27.25 26.75
26 27.25
27
27.25 26.75
17.1
17.3 17.0
17.4
17.2 17.2 17.3 17.3
17.4
17.3
.....
(a) Compute the coefficient of determination, R?.
R?
% (Round to one decimal place as needed.)
(b) Interpret the coefficient of determination.
Approximately % of the variation in
is explained by the least-squares
gression model.
(Round to one decimal place as needed.)
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 0.883 and the least squares regression line is y = 0.134x + 13.693. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.4 27.75 25.25 26 25.25 27.25 26.75 26 27.25 27 27.25 26.75 17.1 17.3 17.0 17.4 17.2 17.2 17.3 17.3 17.4 17.3 ..... (a) Compute the coefficient of determination, R?. R? % (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. Approximately % of the variation in is explained by the least-squares gression model. (Round to one decimal place as needed.)
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