Short definition: A Monte Carlo simulation is a computational technique that uses random sampling and statistical analysis to model the probability of different outcomes in a complex system.
Explanation: Monte Carlo simulations are used to estimate the likelihood of various events or outcomes by running a large number of trials with different input values. This method is particularly useful when dealing with uncertain or complex systems where analytical solutions are difficult or impossible to obtain.
Example: A financial analyst might use a Monte Carlo simulation to model the potential range of returns for a stock portfolio over a given time period, taking into account various factors such as historical market data, economic forecasts, and company-specific risks.
Additional information (optional): Monte Carlo simulations are widely used in fields such as finance, engineering, physics, and environmental science. They can be used to model a wide range of phenomena, from the spread of infectious diseases to the performance of complex engineering systems.