For each uncertain variable in a simulation, or assumption, you define the possible values with a probability distribution. The type of distribution you select depends on the conditions surrounding the variable. Common distribution types are normal, triangular, uniform, and lognormal, as shown in Figure 5, Common Distribution Types.
During a simulation, Crystal Ball calculates numerous scenarios of a model by repeatedly picking values from the probability distribution for the uncertain variables and using those values for each assumption cell. Commonly, a Crystal Ball simulation calculates hundreds or thousands of scenarios, or trials, in just a few seconds. The value to use for each assumption for each trial is selected randomly from the defined possibilities.
Because distributions for independent variables are so important to simulations, selecting and applying the appropriate distribution is the main part of defining an assumption cell. For more information on probability distributions, see Understanding Probability Distributions.
For more information about assumptions, see the other topics in Defining Model Assumptions.