The article presents a method to handle problems with data outliers and collinearity in statistical models. The researchers used Principal Component Regression and robust weighting functions to address these issues. They tested the method on real data from a cement factory and found that the variables indeed had collinearity problems. By applying the weighted regression approach, they were able to effectively deal with both outliers and collinearity in the data.