The least squares regression line minimizes the sum of the
A)differences between actual and predicted y values.
B)absolute deviations between actual and predicted y values.
C)absolute deviations between actual and predicted x values.
D)squared differences between actual and predicted y values.

Question

Quizplus · Accepted Answer

The least squares regression line is designed to minimize the sum of squared differences between actual and predicted y values. This is because the sum of squared differences gives an indication of how much the regression line is deviating from the actual data points. By minimizing this sum, the line is able to best fit the data and make accurate predictions.

The Least Squares Regression Line Minimizes the Sum of the