  Monte Carlo simulations are widely used in many areas including particle
accelerators. In this lecture, after a short introduction and reviewing of some
statistical backgrounds, we will discuss methods such as direct inversion,
rejection method, and Markov chain Monte Carlo to sample a probability
distribution function, and methods for variance reduction to evaluate numerical
integrals using the Monte Carlo simulation. We will also briefly introduce the
quasi-Monte Carlo sampling at the end of this lecture.
