Weighted least squares is the method of estimation in which the estimates arise from minimizing the weighted sum of squares of the differences between response variable and its predicted value in terms of the model of interest. It is often used when the variance of response variable is thought to change over range of values of the explanatory variable(s), in which case the weights are usually taken as the reciprocals of the variance.