Simulation uses a representation or model of a system to analyze the expected behavior or performance of the system.
Monte Carlo analysis simulates a model's outcome many times to provide a statistical distribution of the calculated results. To use a Monte Carlo simulation, you must have three estimates (most likely, pessimistic, and optimistic) plus an estimate of the likelihood of the estimate being between the most likely and optimistic values
Steps of the Monte Carlo Analysis:
1. Assess the range for the variables being considered
2. Determine the probability distribution of each variable
3. For each variable, select a random value based on the probability distribution
4. Run a deterministic analysis or one pass through the model
5. Repeat steps 3 and 4 many times to obtain the probability distribution of the model's results