There's a point he omitted: In curve fitting, exploratory data analysis, data mining, etc., we are looking for X. We don't know if X exists. But if X does exi

There's a point he omitted: In curve fitting, exploratory data analysis, data mining, etc., we are looking for X. We don't know if X exists. But if X does exist, then our methods have a shot at finding X. So, we look. Maybe we find something. We test what we find, and it appears to work as we believe X would. So, we start to believe that X exists and we have found it. Do like following this 'paradigm'? No! But, when people do follow this paradigm and claim to have found X, then I can't be sure they are wrong! E.g., maybe there is a statistical model that predicts the stock market. So, do a lot of curve fitting. Find something that appears to predict. Then if there is a predictive model, maybe have found it. Test the model on old data not used in constructing the model and see if it works. If it does, then we start to believe that there is a predictive model and that we have found it or something close enough. When people do such things, I can't say that they are wrong.