Monte Carlo simulation is a method of assessing risk characteristics of a system with uncertainty where assumptions are repeatedly sampled based on predefined probability distributions and a probability distribution of the related output, or answer we are looking for is generated. This facilitates answering questions about the future in terms of probabilities rather than single deterministic "answers".
Palisades @Risk is part of the Palisades Decision Suite, a sophisticated software package add-in for Excel. @Risk is used to perfrom Monte Carlo analysis and can be used in any spreadsheet model where uncertainty is expected and probability distributions can be estimated to model that uncertainty.
Monte Carlo simulation is fairly complex with many possible contingencies. The tutorial presented below is suitable as an introduction to Monte Carlo simulation and covers:
The spreadsheet used in the video can be downloaded here.