Method of Moments to Fit Distributions from Data

Learn the method of moments, a fundamental statistical technique for estimating probability distribution parameters from sample data by matching theoretical moments with sample moments. Explore the intuitive approach of using sample statistics like mean and variance to solve for unknown parameters in probability models. Work through practical examples demonstrating how to apply this method to fit Poisson distributions by estimating the decay rate lambda, and normal distributions by determining mean and variance parameters. Understand the mathematical foundations behind moment matching and gain hands-on experience with parameter estimation techniques commonly used in statistical modeling and data analysis.