Almost all areas of the sciences use models to study and predict physical phenomena, but predictions and conclusions are only as good as the models on which they are based. The statistical assessment of errors in model prediction and model estimation is of fundamental importance. Recent reports of the Intergovernmental Panel on Climate Change (IPCC), for example, present and interpret several commonly used estimates of average error to evaluate and compare the accuracies of global climate model simulations [Flato et al., 2013].