ABSTRACT
This chapter describes some methods for analyzing data using the probability concepts such as the role of randomness in representing uncertainty when using a model to describe a system. To build a representative simulation model that accounts for uncertain parameter values, input parameters are modeled as values that are randomly distributed. In constructing a model, one may realize that many elements in a model must be characterized with an input that exhibits some degree of uncertainty. These can include entity arrival times, number of entities arriving, activity durations, number of resources in a pool, capacity of an activity, routing of entities for processing, the cost of a resource, proportion of entities having a specific characteristic, and so forth. Every model input should be considered for its uncertainty. Data elicitation should be treated as a structured interview of multiple experts who make independent judgments about parameter values and then compare them with the intention of developing a consensus.
