This book provides an introduction to probability theory and its applications. The emphasis is on essential probabilistic reasoning, which is illustrated with a large number of samples. The fourth edition adds material related to mathematical finance as well as expansions on stable laws and martingales.

From the reviews: "Almost thirty years after its first edition, this charming book continues to be an excellent text for teaching and for self study." -- STATISTICAL PAPERS

This is an introductory textbook on probability theory and its applications. Basic concepts such as probability measure, random variable, distribution, and expectation are fully treated without technical complications. Both the discrete and continuous cases are covered, the elements of calculus being used in the latter case. The emphasis is on essential probabilistic reasoning, amply motivated, explained, and illustrated with a large number of carefully selected examples. Special topics include combinatorial problems, urn schemes, Poisson processes, random walks, genetic models, and Markov chains. Problems with solutions are provided at the end of each chapter. Its easy style and full discussion make this a useful text not only for mathematics and statistics majors, but also for students in engineering and physical, biological, and social sciences. This edition adds two new chapters covering applications to mathematical finance. Elements of modern portfolio and option theories are presented in a detailed and rigorous manner. The approach distinguishes this text from other more mathematically advanced treatises or more technical manuals. Kai Lai Chung is Professor Emeritus of Mathematics at Stanford University. Farid AitSahlia is a Senior Scientist with DemandTec, where he develops econometric and optimization methods for demand-based pricing models. He is also a visiting scholar in the department of statistics at Stanford University, where he obtained his Ph.D.in operations research.