Weighted Least Square (WLS) regression models are fundamentally different from the Ordinary Least Square Regression (OLS) . WLS is used when the error terms are not homoskedastic. Ordinary least squares (OLS) assumes that there is constant variance in the errors (which is called homoscedasticity)
The method of weighted least squares can be used when the ordinary least squares assumption of constant variance in the errors is violated (which is called heteroscedasticity)
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