Product Description

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.

Product Details

• Amazon Sales Rank: #584203 in Books
• Published on: 2006-07-14
• Original language: English
• Number of items: 1
• Binding: Hardcover
• 384 pages

Review

"In spite of the original edition of the book being nearly thirty years old, the text still has its role to play in first and second year undergraduate probability courses. It provides an excellent foundation to more advanced courses in the subject."
Short Book Reviews, Vol. 23/3, Dec. 2003

"This edition is the third revision of a text on mathematical probability first published in 1974. The text is aimed at undergraduate mathematics students and is accessible to a general audience. The prose is accurate, entertaining, and dense with historical tidbits. Two concluding chapters on mathematical finance have been added to the eight chapters in the third edition by the second author." The American Statistician, May 2004

From the reviews of the fourth edition:

"The main novelty in the fourth edition of this well-written book is the addition of new chapters … . The new chapters share the friendly yet rigorous style of the former ones. They begin with an account of the financial vocabulary, which is then expounded in probabilistic terms. … Almost thirty years after its first edition, this charming book continues to be an excellent text for teaching and for self study." (Ricardo Maronna, Statistical Papers, Vol. 45 (4), 2004)

Customer Reviews

Probability
Did not recieve the item in two days when I paid extra for expedited shipping. Recieved it 3 weeks later

A very good book indeed
A reviewer who has given this book 2 stars below says "It was the only math textbook that I really struggled with". That tells me this guy shouldn't have been in a maths course in the first place; stick to drama or English dude, they may be a little taxing for your brain. There should be a rule on Amazon against letting idiots review books of substance.

Chung's book is rich in historical notes, motivation and intuitive development of the subject. Chung is a world-renowned probabilst and also is a gifted writer. This book was followed in my undergraduate days and I still have fond memories of it.

My only gripe is that the new edition has added stuff by another author on finance. There was no need for this whatsoever.

best textbook for elementary probability theory
As a professor in computer science, I am teaching a seminar course in which I wanted to cover basic probability theory in a week. I read at least a half dozen textbooks in the university library and found this book to be far better than others for my purpose. In particular, the material I used was the derivation from the binomial distribution (a coin toss) to the normal and the Poisson distributions, which I covered in two classes. Students liked the many interesting, real-life examples in the book. In addition, I taught the two proofs for the law of large numbers. The second one from Chebyshev was more powerful (applies to non-identical distributions), stronger (guaratees the speed of convergence), simpler and shorter (half a page with no need of mathematical analysis). It eclipsed the theories of other mathematicians in the previous 200 years. The Chebyshev's theorem was new to me and to all the people I mentioned this to.

Of the books I know, this is the best entry level textbook for probability theories. I did not read the chapters on mathematical finance.