This document summarizes Monte Carlo integration techniques, including importance sampling and Markov chain Monte Carlo. It defines Monte Carlo integration as a numerical integration method using random numbers. The techniques were originally developed around 1944 to study the atomic bomb. Common uses are for evaluating integrals. The document outlines the basic steps of Monte Carlo methods and defines importance sampling as estimating properties of one distribution using samples from another similar distribution to reduce variance. It also defines Markov chain Monte Carlo as using a Markov chain to simulate samples from a target posterior probability distribution.