Surprisingly, many statisticians see cross-validation as something data miners do, but not a core statistical technique. I thought it might be helpful to summarize the role of cross-validation in statistics, especially as it is proposed that the Q&A site at stats.stackexchange.com should be renamed CrossValidated.com. Cross-validation is primarily a way of measuring the predictive performance of a statistical model. Every statistician knows that the model fit statistics are not a good guide to how well a model will predict: high $R^2$ does not necessarily mean a good …