Statistical model: We use a statistical model to tell us that a certain behavior or sequence of behaviors is very unlikely, or very unlikely in response to a specific action. The behavior is not impossible, but it is suspicious. We can test whether the actual behavior in the test is within the tolerance limits predicted by the model. This is often useful for looking for patterns in larger sets of data (longer sequences of tests). For example, suppose we expect an eCommerce website to get 80% of its customers from the local area, but in beta trials of its customer-analysis software, the software reports that 70% of the transactions that day were from far away. Maybe this was a special day, but probably this software has a bug. If we can predict a statistical pattern (correlations among variables, for example), we can check for it.