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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.

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For more information on Monte Carlo simulation, see Monte Carlo Simulation, page 141.

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