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.
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.
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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The options for part b are: head circumference or height
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