This is a graduate textbook in Statistical Physics intended for students in Physics, Biophysics, Chemistry, Materials Science, and Engineering. It is based on using computer simulations in Python as a learning tool. Many exercises involve simulations, and a set of listings of computer programs are given in the appendix. Algorithms discussed include molecular dynamics, Metropolis Monte Carlo, Gibbs ensemble, and the Wolff algorithm.About the Author: Leonard M. Sander is Professor of Physics and Complex Systems at the University of Michigan, Ann Arbor. His research interests include pattern formation, non-equilibrium statistical physics, and biophysics.