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The weight (in pounds) and height (in inches) for a child were measured every few months over a two-year period. The results are displayed in the scatterplot. The equation ý = 17.4 + 0.5x is called the least-squares regression line because it O is least able to make accurate predictions for the A Child's Weight and Height data. O makes the strongest association between weight and height. 40 36 O minimizes the sum of the squared distances from the actual y-value to the predicted y-value. 32 maximizes the sum of the squared distances from the actual y-value to the predicted y-value. 24 20 68 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 Height (Inches)

The weight (in pounds) and height (in inches) for a child were measured every few months over a two-year period. The results are displayed in the scatterplot. The equation ý = 17.4 + 0.5x is called the least-squares regression line because it O is least able to make accurate predictions for the A Child's Weight and Height data. O makes the strongest association between weight and height. 40 36 O minimizes the sum of the squared distances from the actual y-value to the predicted y-value. 32 maximizes the sum of the squared distances from the actual y-value to the predicted y-value. 24 20 68 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 Height (Inches)

Linear Algebra: A Modern Introduction
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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The weight (in pounds) and height (in inches) for a child were measured every few months over a two-year period. The results are displayed in the scatterplot. The equation ý = 17.4 + 0.5x is called the least-squares regression line because it O is least able to make accurate predictions for the A Child's Weight and Height data. O makes the strongest association between weight and height. 40 36 O minimizes the sum of the squared distances from the actual y-value to the predicted y-value. O maximizes the sum of the squared distances from the actual y-value to the predicted y-value. 32 24 20 68 10 12 14 16 18 20 22 24 26 28 30 32 34 3638 40 42 Weight (Pounds) Height (Inches)
Transcribed Image Text:The weight (in pounds) and height (in inches) for a child were measured every few months over a two-year period. The results are displayed in the scatterplot. The equation ý = 17.4 + 0.5x is called the least-squares regression line because it O is least able to make accurate predictions for the A Child's Weight and Height data. O makes the strongest association between weight and height. 40 36 O minimizes the sum of the squared distances from the actual y-value to the predicted y-value. O maximizes the sum of the squared distances from the actual y-value to the predicted y-value. 32 24 20 68 10 12 14 16 18 20 22 24 26 28 30 32 34 3638 40 42 Weight (Pounds) Height (Inches)
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