Probability and Random Variables
MIT OpenCourseWare's introduction to probability theory covers distribution functions and the standard discrete and continuous distributions: binomial, geometric, hypergeometric, and Poisson, along with uniform, exponential, normal, gamma, and beta. Students work through conditional probability, Bayes theorem, joint distributions, the Chebyshev inequality, the law of large numbers, and the central limit theorem. As with other MIT OCW offerings, the course provides lecture materials, problem sets, and exams from an actual MIT course, free to access with no enrollment fee and no certificate offered. It suits students who have completed single-variable calculus and want a rigorous grounding in probability before moving into statistics, stochastic processes, or applied fields that depend on random variable theory.