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Mathematics of Probability

Daniel W. Stroock Massachusetts Institute of Technology, Cambridge, MA
Available Formats:
Hardcover ISBN: 978-1-4704-0907-4
Product Code: GSM/149
List Price: $80.00 MAA Member Price:$72.00
AMS Member Price: $64.00 Electronic ISBN: 978-1-4704-1027-8 Product Code: GSM/149.E List Price:$75.00
MAA Member Price: $67.50 AMS Member Price:$60.00
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List Price: $120.00 MAA Member Price:$108.00
AMS Member Price: $96.00 Click above image for expanded view Mathematics of Probability Daniel W. Stroock Massachusetts Institute of Technology, Cambridge, MA Available Formats:  Hardcover ISBN: 978-1-4704-0907-4 Product Code: GSM/149  List Price:$80.00 MAA Member Price: $72.00 AMS Member Price:$64.00
 Electronic ISBN: 978-1-4704-1027-8 Product Code: GSM/149.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: 1492013; 284 pp
MSC: Primary 60;

This book covers the basics of modern probability theory. It begins with probability theory on finite and countable sample spaces and then passes from there to a concise course on measure theory, which is followed by some initial applications to probability theory, including independence and conditional expectations. The second half of the book deals with Gaussian random variables, with Markov chains, with a few continuous parameter processes, including Brownian motion, and, finally, with martingales, both discrete and continuous parameter ones.

The book is a self-contained introduction to probability theory and the measure theory required to study it.

Graduate students and researchers interested in probability.

• Chapters
• Chapter 1. Some background and preliminaries
• Chapter 2. Probability theory on uncountable sample spaces
• Chapter 3. Some applications to probability theory
• Chapter 4. The central limit theorem and Gaussian distributions
• Chapter 5. Discrete parameter stochastic processes
• Chapter 6. Some continuous-time processes
• Chapter 7. Martingales

• Reviews

• ... I regard this book highly, and I recommend it for course use as well as for independent study.

MAA Reviews
• This book is a very thorough advanced undergraduate/beginning graduate course on probability theory for students who have a good background in modern mathematical ideas. ... [W]hat distinguishes this book from its many competitors is the thoroughness of argument, and the tasteful choice of auxiliary topics that complement the main menu. ... The book is replete with carefully chosen exercise for readers to test their understanding. Another nice touch is that the author always takes care to let the reader know who originally came up with a particularly clever argument or method. In this way, readers get a healthy exposure to ways of thinking originating from Doeblin, Doob, Dynkin, Huygens, Kac, Kolmogorov, Livy, Marcinkiewicz and Wiener, among many others. This is a very good book on which to base a graduate course or to use for self-study.

David Applebaum, University of Sheffield, South Yorkshire, UK
• Mathematics of Probability is a very enjoyable book. It is definitely a book for graduate students, but it manages to begin exploring the subject without a lot of prerequisites. ... It manages to discuss rigorously, and in a mostly self-contained manner, advanced topics which are not found in undergraduate books. ... It is a good book for independent study. It does not overwhelm the reader with exercises (each section ends with several problems). The footnotes and the comments at the end of each chapter are to the point and help the reader keep focus. ... All in all, I regard this book highly and I recommend it for course use as well as for independent study.

Florin Catrina, MAA Reviews
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• Get Permissions
Volume: 1492013; 284 pp
MSC: Primary 60;

This book covers the basics of modern probability theory. It begins with probability theory on finite and countable sample spaces and then passes from there to a concise course on measure theory, which is followed by some initial applications to probability theory, including independence and conditional expectations. The second half of the book deals with Gaussian random variables, with Markov chains, with a few continuous parameter processes, including Brownian motion, and, finally, with martingales, both discrete and continuous parameter ones.

The book is a self-contained introduction to probability theory and the measure theory required to study it.

Graduate students and researchers interested in probability.

• Chapters
• Chapter 1. Some background and preliminaries
• Chapter 2. Probability theory on uncountable sample spaces
• Chapter 3. Some applications to probability theory
• Chapter 4. The central limit theorem and Gaussian distributions
• Chapter 5. Discrete parameter stochastic processes
• Chapter 6. Some continuous-time processes
• Chapter 7. Martingales
• ... I regard this book highly, and I recommend it for course use as well as for independent study.

MAA Reviews
• This book is a very thorough advanced undergraduate/beginning graduate course on probability theory for students who have a good background in modern mathematical ideas. ... [W]hat distinguishes this book from its many competitors is the thoroughness of argument, and the tasteful choice of auxiliary topics that complement the main menu. ... The book is replete with carefully chosen exercise for readers to test their understanding. Another nice touch is that the author always takes care to let the reader know who originally came up with a particularly clever argument or method. In this way, readers get a healthy exposure to ways of thinking originating from Doeblin, Doob, Dynkin, Huygens, Kac, Kolmogorov, Livy, Marcinkiewicz and Wiener, among many others. This is a very good book on which to base a graduate course or to use for self-study.

David Applebaum, University of Sheffield, South Yorkshire, UK
• Mathematics of Probability is a very enjoyable book. It is definitely a book for graduate students, but it manages to begin exploring the subject without a lot of prerequisites. ... It manages to discuss rigorously, and in a mostly self-contained manner, advanced topics which are not found in undergraduate books. ... It is a good book for independent study. It does not overwhelm the reader with exercises (each section ends with several problems). The footnotes and the comments at the end of each chapter are to the point and help the reader keep focus. ... All in all, I regard this book highly and I recommend it for course use as well as for independent study.

Florin Catrina, MAA Reviews
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