The standard approach to regression analysis wherein the goal is to minimize the sum of squares of the deviations between actual and predicted values in the calibration data.  Because of its statistical properties, it has become the predominant method for regression analysis. However, it has not been shown to produce more accurate forecasts than least absolute values.