## DEFINITION of 'Least Squares'

A statistical method used to determine a line of best fit by minimizing the sum of squares created by a mathematical function. A "square" is determined by squaring the distance between a data point and the regression line. The least squares approach limits the distance between a function and the data points that a function is trying to explain. It is used in regression analysis, often in nonlinear regression modeling in which a curve is fit into a set of data.

## BREAKING DOWN 'Least Squares'

The least squares approach is a popular method for determining regression equations. Instead of trying to solve an equation exactly, mathematicians use the least squares to make a close approximation (referred to as a maximum-likelihood estimate). Modeling methods that are often used when fitting a function to a curve include the straight line method, polynomial method, logarithmic method and Gaussian method.