Introduction to probability / Joseph K. Blitzstein, Harvard University Cambridge, Massachusetts and Jessica Hwang, Stanford University Stanford, California.

Includes bibliographic references and index.

Probability and counting -- Conditional probability -- Random variables and their distributions -- Expectation -- Continuous random variables -- Moments -- Joint distributions -- Transformations -- Conditional expectation -- Inequalities and limit theorems -- Markov chains -- Markov chain Monte Carlo -- Poisson processes.

"Undergraduate probability book that assumes one-semester of calculus. One key is the emphasis on "stories" for the probability distributions (which I mean in both an intuitive and technical sense): there are a dozen or so key distributions (Normal, Binomial, Poisson, etc.) that are incredibly widely-used in statistics, but a lot of books just write down formulas for them without explaining clearly why these particular distributions are so important, or how they are all connected. Each of these distributions has a "story" (a natural application where it arises), and thinking about stories makes the distributions easier to remember, understand, and work with"-- Provided by publisher.

Description based on print version record and CIP data provided by publisher.