The weight (in pounds) and height (in inches) for a childwere measured every few months over a two-yearperiod. The results are displayed in the scatterplot.The equation ŷ = 17.4 + 0.5x is called the least-squaresregression line because itis least able to make accurate predictions for thedata.A Child's Weight and Heightmakes the strongest association between weight and40height.36minimizes the sum of the squared distances from theactual y-value to the predicted y-value.32maximizes the sum of the squared distances fromthe actual y-value to the predicted y-value.2024206 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42Weight (Pounds)Height (Inches)

In the least-squares method we minimizes the sum of the squared vertical difference between line and…

The equation ŷ = 17.4 + 0.5x is called the least-squares regression line because it is least able to make accurate predictions for the data. makes the strongest association between weight and height. 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.

The equation ŷ = 17.4 + 0.5x is called the least-squares regression line because it is least able to make accurate predictions for the data. makes the strongest association between weight and height. 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.

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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