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Knowing the Odds: An Introduction to Probability

John B. Walsh University of British Columbia, Vancouver, BC, Canada
Available Formats:
Hardcover ISBN: 978-0-8218-8532-1
Product Code: GSM/139
List Price: $80.00 MAA Member Price:$72.00
AMS Member Price: $64.00 Electronic ISBN: 978-0-8218-9031-8 Product Code: GSM/139.E List Price:$75.00
MAA Member Price: $67.50 AMS Member Price:$60.00
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This product is available for purchase as a bundle. Purchasing as a bundle enables you to save on the electronic version.
List Price: $120.00 MAA Member Price:$108.00
AMS Member Price: $96.00 Click above image for expanded view Knowing the Odds: An Introduction to Probability John B. Walsh University of British Columbia, Vancouver, BC, Canada Available Formats:  Hardcover ISBN: 978-0-8218-8532-1 Product Code: GSM/139  List Price:$80.00 MAA Member Price: $72.00 AMS Member Price:$64.00
 Electronic ISBN: 978-0-8218-9031-8 Product Code: GSM/139.E
 List Price: $75.00 MAA Member Price:$67.50 AMS Member Price: $60.00 Bundle Print and Electronic Formats and Save! This product is available for purchase as a bundle. Purchasing as a bundle enables you to save on the electronic version.  List Price:$120.00 MAA Member Price: $108.00 AMS Member Price:$96.00
• Book Details

Volume: 1392012; 421 pp
MSC: Primary 60;

John Walsh, one of the great masters of the subject, has written a superb book on probability. It covers at a leisurely pace all the important topics that students need to know, and provides excellent examples. I regret his book was not available when I taught such a course myself, a few years ago.

Ioannis Karatzas, Columbia University

In this wonderful book, John Walsh presents a panoramic view of Probability Theory, starting from basic facts on mean, median and mode, continuing with an excellent account of Markov chains and martingales, and culminating with Brownian motion. Throughout, the author's personal style is apparent; he manages to combine rigor with an emphasis on the key ideas so the reader never loses sight of the forest by being surrounded by too many trees. As noted in the preface, “To teach a course with pleasure, one should learn at the same time.” Indeed, almost all instructors will learn something new from the book (e.g. the potential-theoretic proof of Skorokhod embedding) and at the same time, it is attractive and approachable for students.

Yuval Peres, Microsoft

With many examples in each section that enhance the presentation, this book is a welcome addition to the collection of books that serve the needs of advanced undergraduate as well as first year graduate students. The pace is leisurely which makes it more attractive as a text.

Srinivasa Varadhan, Courant Institute, New York

This book covers in a leisurely manner all the standard material that one would want in a full year probability course with a slant towards applications in financial analysis at the graduate or senior undergraduate honors level. It contains a fair amount of measure theory and real analysis built in but it introduces sigma-fields, measure theory, and expectation in an especially elementary and intuitive way. A large variety of examples and exercises in each chapter enrich the presentation in the text.

• Chapters
• Chapter 1. Probability spaces
• Chapter 2. Random variables
• Chapter 3. Expectations II: The general case
• Chapter 4. Convergence
• Chapter 5. Laws of large numbers
• Chapter 6. Convergence in distribution and the CLT
• Chapter 7. Markov chains and random walks
• Chapter 8. Conditional expectations
• Chapter 9. Discrete-parameter martingales
• Chapter 10. Brownian motion

• Requests

Review Copy – for reviewers who would like to review an AMS book
Desk Copy – for instructors who have adopted an AMS textbook for a course
Examination Copy – for faculty considering an AMS textbook for a course
Permission – for use of book, eBook, or Journal content
Accessibility – to request an alternate format of an AMS title
Volume: 1392012; 421 pp
MSC: Primary 60;

John Walsh, one of the great masters of the subject, has written a superb book on probability. It covers at a leisurely pace all the important topics that students need to know, and provides excellent examples. I regret his book was not available when I taught such a course myself, a few years ago.

Ioannis Karatzas, Columbia University

In this wonderful book, John Walsh presents a panoramic view of Probability Theory, starting from basic facts on mean, median and mode, continuing with an excellent account of Markov chains and martingales, and culminating with Brownian motion. Throughout, the author's personal style is apparent; he manages to combine rigor with an emphasis on the key ideas so the reader never loses sight of the forest by being surrounded by too many trees. As noted in the preface, “To teach a course with pleasure, one should learn at the same time.” Indeed, almost all instructors will learn something new from the book (e.g. the potential-theoretic proof of Skorokhod embedding) and at the same time, it is attractive and approachable for students.

Yuval Peres, Microsoft

With many examples in each section that enhance the presentation, this book is a welcome addition to the collection of books that serve the needs of advanced undergraduate as well as first year graduate students. The pace is leisurely which makes it more attractive as a text.

Srinivasa Varadhan, Courant Institute, New York

This book covers in a leisurely manner all the standard material that one would want in a full year probability course with a slant towards applications in financial analysis at the graduate or senior undergraduate honors level. It contains a fair amount of measure theory and real analysis built in but it introduces sigma-fields, measure theory, and expectation in an especially elementary and intuitive way. A large variety of examples and exercises in each chapter enrich the presentation in the text.

• Chapters
• Chapter 1. Probability spaces
• Chapter 2. Random variables
• Chapter 3. Expectations II: The general case
• Chapter 4. Convergence
• Chapter 5. Laws of large numbers
• Chapter 6. Convergence in distribution and the CLT
• Chapter 7. Markov chains and random walks
• Chapter 8. Conditional expectations
• Chapter 9. Discrete-parameter martingales
• Chapter 10. Brownian motion
Review Copy – for reviewers who would like to review an AMS book
Desk Copy – for instructors who have adopted an AMS textbook for a course
Examination Copy – for faculty considering an AMS textbook for a course
Permission – for use of book, eBook, or Journal content
Accessibility – to request an alternate format of an AMS title
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