Learn how Monte Carlo Simulation models uncertainty, predicts possible outcomes, and supports data-driven decision-making in complex systems.
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Monte Carlo Simulation is a statistical method used to model uncertainty and estimate possible outcomes based on random variables and probability distributions.
In this module, you will learn how to build simulation models, work with variable input factors, and evaluate risks in uncertain environments. Monte Carlo methods support decision-making by simulating thousands of scenarios and identifying probable outcomes.
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