Markov Chain Monte Carlo (MCMC)

Markov Chain Monte Carlo (MCMC) is a statistical method used to sample from complex probability distributions. Imagine trying to understand the behavior of a crowd in a park by randomly visiting different spots. MCMC does something similar—it creates a sequence of random samples based on a specific set of rules that reflects how likely different outcomes are. Over time, these samples approximate the desired distribution, allowing researchers to estimate values or make predictions without needing to see the entire dataset. It's widely used in fields like statistics, machine learning, and physics to analyze complex systems.