Weighted least squares

Weighted least squares (WLS) is a statistical method used to improve the accuracy of regression analysis. In WLS, different data points are given different levels of importance, or "weights," based on their reliability or variability. This means that more trustworthy observations have a stronger influence on the overall model. For example, if some measurements are more precise than others, WLS allows for a better fit to the data by emphasizing those precise measurements, leading to more accurate predictions and insights. It is particularly useful when data points have different variabilities.