Comparison of ordinary least squares (OLS), weighted least squares (WLS) and generalized least squares regression analysis from Monte Carlo data. Hyper-ellipsoids are generated to indicate the corresponding 95% confidence regions (CRs) and reveals that the highest accuracy scheme is that of a GLS which has the smallest CR which corresponds to a high degree of certainty of the range of possible values, followed by a WLS which has a slightly lower accuracy compared to a GLS, and finally a OLS which has the lowest accuracy as the CR is unduly large.