Abstract
Validation of two types of models are discussed: functional and structural. The former are predictive, the latter presume to represent reality with great accuracy. To validate a model its predictions must be compared with observable data, which calls for accurate use of statistics. This application of inferential statistics is briefly discussed, along with the problems of experimental design.