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Monte Carlo Simulation, Monte Carlo methods (or Monte Carlo experiments) are a broad class of computational algorithms that depend on regular random sampling to obtain numerical outcomes. Their important idea is applying randomness to resolve difficulties that might be deterministic in principle. They are repeatedly used in physical and mathematical problems and are most convenient when it is difficult or impossible to use other ways. Monte Carlo techniques are used primarily in three problem classes: optimisation, numerical integration, and generating draw out of a probability distribution.
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