This section discusses various methods that can be used to help validate the quality and predictive capabilities of a model. Some techniques can be carried out during a model's construction which will help ensure that the finished model is as free from errors and as accurate and useful as possible. Other techniques can only be executed at a future time when some of the model's predictions can be compared against what actually happened but one may nonetheless devise a plan to help facilitate that comparison.
Key points to consider are:
Does the model meet management needs?
Is the model free from errors?
Are the model's predictions robust?
The following topics describe the methods we use to help answer these questions: