The least-squares method for determining the best fit minimizes the:
A) total variation in the dependent variable.
B) sum of squares for regression.
C) sum of squares for error.
D) sum of squares for the x-values.

Question

Quizplus · Accepted Answer

The least-squares method aims to minimize the sum of squares for error, which represents the difference between the observed values and the predicted values. This is done by adjusting the parameters of the regression equation to see which line best fits the data. Minimizing the sum of squares for error ensures that the regression line is as close to the actual data points as possible.

The Least-Squares Method for Determining the Best Fit Minimizes The