The least squares method is the criterion of best fit most commonly used in linear regression. This method is based on

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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ISBN:9780079039897
Author:Carter
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Chapter4: Equations Of Linear Functions
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23)
The least squares method is the criterion of best fit most commonly used in linear regression.
This method is based on
O minimizing the errors made in prediction by the regression line.
O minimizing the correlation coefficient.
O maximizing the number of points that the regression line passes through.
minimizing the sum of squared errors between the data points and regression line.
Transcribed Image Text:The least squares method is the criterion of best fit most commonly used in linear regression. This method is based on O minimizing the errors made in prediction by the regression line. O minimizing the correlation coefficient. O maximizing the number of points that the regression line passes through. minimizing the sum of squared errors between the data points and regression line.
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