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Monte Carlo simulation is a technique used to understand the impact of risk
and uncertainty in financial, project management, cost, and other forecasting models.
A problem solving technique used to approximate the probability of certain outcomes by running multiple trial runs, called simulations, using random variables.
As mentioned above, its used to calculate the uncertainty assuming normal distribution or three points estimate, in project management we use it to calculate budget and schedule risk.
Moreover; I would like to add, that there is a plugin in Excel that enable you to do Monte Carlo analysis, the plugin is called (CrystalBall) its developed by Oracle and you can download it for30 days as a free trial
Monte Carlo simulation, or probability simulation, is a technique used to understand the impact of risk
and uncertainty in financial, project management, cost, and other forecasting models
In a Monte Carlo simulation, a random value is selected for each of the tasks, based on the range of
estimates. The model is calculated based on this random value. The result of the model is recorded,
and the process is repeated. A typical Monte Carlo simulation calculates the model hundreds or
thousands of times, each time using different randomly-selected values.
When the simulation is complete, we have a large number of results from the model, each based on
random input values. These results are used to describe the likelihood, or probability, of reaching
various results in the model.
It is used in case of uncertainty for probability distribution of variables to get the expected result of time or cost
Monte Carlo simulation is a problem solving technique used to approximate the probability of certain outcomes by running multiple trial runs, called simulations, using random variables. It is a technique used to understand the impact of risk and uncertainty in financial, project management, cost, and other forecasting models.
In a Monte Carlo simulation, a random value is selected for each subject task (e.g., time to complete a particular project). The model is calculated hundreds or thousands of times, each time using different randomly-selected values and the results of each calculation is recorded. When the simulation is complete, the results are used to describe the likelihood, or probability, of reaching various results in the model.
Like any forecasting model, the simulation will only be as good as the estimates you make. It represents probabilities and not certainty but it can be a valuable tool when forecasting an unknown future.
thanks too much and appologize to you for not answer because I am not specialist
