Probability and Random Variables
A foundational probability course from MIT OpenCourseWare covering distribution functions and discrete distributions such as binomial, geometric, hypergeometric, and Poisson, alongside continuous distributions including uniform, exponential, normal, gamma, and beta. The syllabus works through conditional probability, Bayes theorem, joint distributions, the Chebyshev inequality, the law of large numbers, and the central limit theorem. Materials follow MIT OpenCourseWare's standard format of lecture notes, assignments, and exams drawn from an actual MIT course, free to access under a Creative Commons license with no certificate offered. The course suits students who have completed calculus and want a rigorous grounding in probability theory before moving into statistics, stochastic processes, or applied fields like engineering and economics that depend on these tools.