1. Appendix A. Distributions

Data is seldom in a form ready for use in a simulation model. Usually some analysis and conversion needs to be performed for the data to be useful as an input parameter to the simulation. Random phenomena must be fitted to some standard, theoretical distribution such as a normal or exponential distribution (Law and Kelton, 1991), or be input as a frequency distribution.

To define a distribution using a theoretical distribution requires that the data, if available, be fit to an appropriate distribution that best describes the variable. An alternative to using a standard theoretical distribution is to summarize the data in the form of a frequency distribution that can be used directly in the model. A frequency distribution is sometimes referred to as an empirical or user-defined distribution.

Whether fitting data to a theoretical distribution, or using an empirical distribution, it is often useful to organize the data into a frequency distribution table. Defining a frequency distribution is done by grouping the data into intervals and stating the frequency of occurrence for each particular interval. To illustrate how this is done, the following frequency table tabulates the number and frequency of observations for a particular task requiring a certain range of time to perform.