Least squares criterion

Definition

The least squares criterion is used to find an equation (usually linear) that minimizes the sum of squared differences between observed and predicted values.

Related terms

Residuals: Residuals are the differences between observed values and predicted values in a regression analysis.

Regression Line: The regression line is the line that best fits a set of data points using the least squares criterion.

Coefficient of Determination (R-squared): R-squared measures how well a regression model fits the data, ranging from 0 to 1.