6.3702
Introduction to Probability
An introduction to probability theory, the modeling and analysis of probabilistic systems, and elements of statistical inference. Probabilistic models, conditional probability. Discrete and continuous random variables. Expectation and conditional expectation, and further topics about random variables. Limit Theorems. Bayesian estimation and hypothesis testing. Elements of classical statistical inference. Bernoulli and Poisson processes. Markov chains. Students taking graduate version complete additional assignments.
Prerequisites & course information
Subject meets with 6.3700 Prereq: Calculus II (GIR) G (Fall, Spring) 4-0-8 units Credit cannot also be received for 18.600
Sources
- Course catalogue ↗2026–2027