Having built quite a few statistical models myself, I know that it’s hard to do, in part because there are two sorts of errors one can make. This is slightly technical—there’s a longer discussion in The Signal and the Noise if you want to go deeper—but one problem is called “overfitting.” Basically, that means trying to accommodate every nook and cranny in the dataset, sometimes through highly contrived strategies.
