Hardcover ISBN:  9780821885321 
Product Code:  GSM/139 
List Price:  $80.00 
MAA Member Price:  $72.00 
AMS Member Price:  $64.00 
Electronic ISBN:  9780821890318 
Product Code:  GSM/139.E 
List Price:  $75.00 
MAA Member Price:  $67.50 
AMS Member Price:  $60.00 

Book DetailsGraduate Studies in MathematicsVolume: 139; 2012; 421 ppMSC: 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 potentialtheoretic 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 sigmafields, 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.ReadershipUndergraduate and graduate students interested in probability theory.

Table of Contents

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. Discreteparameter martingales

Chapter 10. Brownian motion


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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 potentialtheoretic 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 sigmafields, 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.
Undergraduate and graduate students interested in probability theory.

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. Discreteparameter martingales

Chapter 10. Brownian motion