Andreas Graefe writes (see here here here): The usual procedure for developing linear models to predict any kind of target variable is to identify a subset of most important predictors and to estimate weights that provide the best possible solution for a given sample. The resulting “optimally” weighted linear composite is then used when predicting […]The post The robust beauty of improper linear models in decision making appeared first on…