People are prone to errors in many aspects of life, including when entering numbers. The effects of these errors can be disastrous, for example when an incorrect number is entered when programming a medical infusion pump or when entering financial information into a system. Designing better systems may help to prevent these errors however, in order to do this we need to understand far more about the types of errors being made, and their causes. Unfortunately, there are very few documented examples of number entry errors and thus many of the studies conducted so far rely upon modelled, not real world data. This paper reports a study that was designed to elicit number entry errors and the subsequent process of creating a taxonomy of errors from the information gathered.