ABSTRACT
This chapter presents the fundamental tools used in statistical analysis. In the context of simulation, these tools are used for the purpose of describing processes that contain components which cannot be reproduced deterministically. The application of statistical models in simulation arises out of an inability to find more satisfactory analytical models. This is the act of statistical inference - the generation of conclusions about the characteristics of the population through an analysis of the corresponding characteristics in a sample. Primarily, random sampling is employed to avoid bias in our conclusions, and to provide a measure of precision for those conclusions in terms of the risk of arriving at an erroneous result. A sampling distribution is a distribution formed by a random variable whose values are themselves random variables. Finding a way to establish the size of the boundaries, and the corresponding probability with which those boundaries apply, is the heart of statistical inference.
