ABSTRACT
Raw experimental data would be meaningless without some form of analysis to provide understanding. We need models to obtain meaning from observable fact. A model combines interpretation and a depiction of a phenomenon. The two fundamental types of models are theoretical and empirical. The former follows from known theoretical laws or principles; they convert raw data to knowledge and are predictive in their own right. If sound new data are at variance with theoretical predictions, the theory must be improved to take experimental evidence into account. Conversely, empirical models do not adhere to any theoretical basis; raw data are used to describe the system response.
