The advanced quantitative risk analysis technique that simulates thousands of project scenarios to predict the probability distribution of completion dates and costs is called Monte Carlo Simulation. This technique is used to model the probability of different outcomes when multiple input variables contain inherent uncertainty, providing a probabilistic forecast instead of a single-point estimate.
The process begins by identifying key project variables that are uncertain, such as the duration of individual project activities or the cost of resources. For each of these uncertain input variables, a probability distribution is defined. A probability distribution mathematically describes the range of all possible values for that variable and the li....
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