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Monte Carlo Simulation
Monte Carlo simulation allows you to replace point estimates
with fuzzy values that reflect your uncertainty. This
helps you characterize the range of potential outcomes in a
business situation and assess the probability of reaching
specific targets.
Uncertain inputs can be modeled using a variety of
distributions including the Uniform, Discrete, Triangular,
Normal, Lognormal, Gamma, Exponential, Beta, Bernoulli, Binomial,
Poisson, and Custom distributions.
Results can be presented as cumulative or frequency
distributions which clearly communicate the range and likelihood
of possible outcomes.
 
For more information on Monte Carlo simulation, see Monte Carlo Simulation, page 141.
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