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The correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. Suppose we use the height x of a child to predict the weight y of the child. We conclude that: O height is generally 80% of a child's weight. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64. the least-squares regression line of y on x would have a slope of 0.8. O about 80% of the time, age will accurately predict weight.

The correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. Suppose we use the height x of a child to predict the weight y of the child. We conclude that: O height is generally 80% of a child's weight. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64. the least-squares regression line of y on x would have a slope of 0.8. O about 80% of the time, age will accurately predict weight.

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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The correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. Suppose we use the height x of a child to predict the weight y of the child. We conclude that: O height is generally 80% of a child's weight. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64. the least-squares regression line of y on x would have a slope of 0.8. about 80% of the time, age will accurately predict weight.
Transcribed Image Text:The correlation between the height and weight of children aged 6 to 9 is found to be about r = 0.8. Suppose we use the height x of a child to predict the weight y of the child. We conclude that: O height is generally 80% of a child's weight. the fraction of variation in weights explained by the least-squares regression line of weight on height is 0.64. the least-squares regression line of y on x would have a slope of 0.8. about 80% of the time, age will accurately predict weight.
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