Introduction to Probability
by Joe Blitzstein · edX
HarvardX's self-paced version of Harvard's Stat 110, taught by Joe Blitzstein. Covers counting and story proofs, conditional probability and Bayes' rule, discrete and continuous random variables, joint distributions, the law of large numbers, the central limit theorem and Markov chains.
More resources on Probability
Introduction to Probability
Learn the fundamentals of probability with this introductory book by Blitzstein & Hwang. Perfect for statistics beginners!
probabilitycourse.com
ProbabilityCourse.com is an online learning resource that provides a structured probability course with clear explanations, worked examples, and practice problems covering topics from basics to advanced theory.
seeing-theory.brown.edu
Seeing Theory is an interactive, browser-based resource from Brown University that uses visual simulations to explain fundamental probability and statistics concepts. It offers interactive demos and explanations on topics like probability, distributions, sampling, the central limit theorem, confidence intervals, hypothesis testing, and Bayesian reasoning.
Bayes Theorem, the geometry of changing beliefs
Grant Sanderson builds Bayes' theorem from a diagram of overlapping populations rather than the formula, using the medical-test and Steve-the-librarian examples. Viewers finish able to reason about how evidence should shift a prior probability.
Information Theory (MIT 6.441)
Graduate introduction to the mathematics of information: entropy, lossless compression, binary hypothesis testing, channel coding and lossy compression. Provides 29 lecture note files that together form a textbook-length treatment, plus problem sets. Prepares you to state and prove the core coding theorems.
Binomial distributions | Probabilities of probabilities, part 1
Animated walkthrough of the binomial distribution, using a product-review example to show how observed successes and failures translate into a probability density over an unknown underlying success rate. Explains where the binomial coefficient comes from.