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Weighted least squares is a method of regression, similar to least squares in that it uses the same minimization of the sum of the residuals:

However, instead of weighting all points equally, they are weighted such that points with a greater weight contribute more to the fit:

Often, wi is given as the inverse of the variance, giving points with a lower variance a greater statistical weight:

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