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The process of generating random variables from a known probability distribution to simulate diverse outcomes in a system.

A mathematical function that provides the probabilities of occurrence of different possible outcomes in an experiment.

A technique for estimating the value of an integral using random sampling.

The process by which Monte Carlo simulation results become closer to the true value as more iterations are performed.

A principle that states that as a sample size grows, its mean gets closer to the average of the whole population.

Methods employed in Monte Carlo simulations to decrease the variance of the simulation results without increasing the number of samples.

A variance reduction technique that involves using negatively correlated variables to decrease the variance of the simulation.

A variance reduction technique that improves estimation precision by exploiting the correlation between the variable of interest and a control variable with a known expected value.

A variance reduction technique that involves changing the probability distribution to draw samples from areas where the integrand is large.