Probability and Statistics
by Morris H. DeGroot, Mark J. Schervish · Morris H. DeGroot, Mark J. Schervish
A standard university textbook developing probability from its axioms through random variables, special distributions, and expectation, then building classical and Bayesian inference on that base. Covers estimation, sampling distributions, hypothesis testing, and linear models.
This link may earn us a small commission at no extra cost to you. Affiliate disclosure
More resources on Probability Distributions
Distributome
An interactive navigator, searchable database, and calculators mapping named probability distributions and the relationships between them. Use it to look up a distribution's properties and to see how families connect through limits and transformations.
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.
Wolfram MathWorld
MathWorld is an online mathematics encyclopedia from Wolfram Research offering detailed, browsable articles on topics across the math spectrum, including algebra, geometry, calculus, and number theory. Each entry includes definitions, theorems, formulas, diagrams, worked examples, and links to further reading.
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.
Khan Academy Probability
Video lessons and practice exercises on random variables, expected value, binomial and geometric distributions, and the normal distribution. After working through it you can compute probabilities and expectations for standard discrete and continuous distributions.
Seeing Theory
An interactive, D3.js-based walkthrough of probability and statistics in six chapters, from basic probability and distributions through frequentist inference, Bayesian inference and regression analysis. Parameters are manipulable, so sampling behaviour and fit are visible directly.