Select all the statements that are true of a least-squares regression line. R measures how much of the variation in Y is explained by X in the estimated linear regression. The regression line is used to predict nonlinear patterns. In the equation of the least-squares regression line, Y is a predicted value when X is known. The slope of the regression line is resistant to outliers. The sum of the squares of the residuals is the smallest sum possible. In the equation of the least-squares regression line, Ý is an observed value when X is known.
Select all the statements that are true of a least-squares regression line. R measures how much of the variation in Y is explained by X in the estimated linear regression. The regression line is used to predict nonlinear patterns. In the equation of the least-squares regression line, Y is a predicted value when X is known. The slope of the regression line is resistant to outliers. The sum of the squares of the residuals is the smallest sum possible. In the equation of the least-squares regression line, Ý is an observed value when X is known.
Chapter3: Polynomial Functions
Section: Chapter Questions
Problem 18T
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Transcribed Image Text:Select all the statements that are true of a least-squares regression line.
R measures how much of the variation in Y is explained by X in the estimated linear regression.
The regression line is used to predict nonlinear patterns.
In the equation of the least-squares regression line, Y is a predicted value when X is known.
The slope of the regression line is resistant to outliers.
The sum of the squares of the residuals is the smallest sum possible.
In the equation of the least-squares regression line, Ý is an observed value when X is known.
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