Ordinary least squares or linear least squares is a method for estimating unknown parameters in statistics. It is a method used in linear regression. The goal of the method is to minimize the difference between the observed responses and the responses predicted by the linear approximation of the data. A smaller difference means that model fits the data better. Ordinary least squares is a special case of a method commonly called least squares. The resulting estimator can be expressed by a simple formula.