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Cambridge Series in Statistical and Probabilistic Mathematics Ser.: Probability : Theory and Examples by Rick Durrett (2010, Hardcover)
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PROBABILITY: THEORY AND EXAMPLES (CAMBRIDGE SERIES IN STATISTICAL AND PROBABILISTIC MATHEMATICS) By Rick Durrett - Hardcover.
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About this product
Product Identifiers
PublisherCambridge University Press
ISBN-100521765390
ISBN-139780521765398
eBay Product ID (ePID)84430253
Product Key Features
Number of Pages440 Pages
LanguageEnglish
Publication NameProbability : Theory and Examples
Publication Year2010
SubjectProbability & Statistics / General
TypeTextbook
Subject AreaMathematics
AuthorRick Durrett
SeriesCambridge Series in Statistical and Probabilistic Mathematics Ser.
FormatHardcover
Dimensions
Item Height1.1 in
Item Weight32.9 Oz
Item Length10.2 in
Item Width7.2 in
Additional Product Features
Edition Number4
Intended AudienceScholarly & Professional
LCCN2010-013387
Reviews'The author has done an extraordinary job in showing not simply what the presented theorems can be used for, but also what they cannot be used for.' Mikls Bna, SIGACT News, 'The author has done an extraordinary job in showing not simply what the presented theorems can be used for, but also what they cannot be used for.' Miklós Bóna, SIGACT News, "The best feature of the book is its selection of examples. The author has done an extraordinary job in showing not simply what the presented theorems can be used for, but also what they cannot be used for." Miklos Bona, SIGACT News, "This book is also an excellent resource. Several interesting and concrete examples are presented throughout the textbook, which will help novices obtain a better understanding of the fundamentals of probability theory." Ramesh Garimella, Computing Reviews
Dewey Edition22
IllustratedYes
Dewey Decimal519.2
Table Of Content1. Measure theory; 2. Laws of large numbers; 3. Central limit theorems; 4. Random walks; 5. Martingales; 6. Markov chains; 7. Ergodic theorems; 8. Brownian motion; Appendix A. Measure theory details.
SynopsisThis classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems. The fourth edition begins with a short chapter on measure theory to orient readers new to the subject., This book is an introduction to probability theory covering laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems.
LC Classification NumberQA273 .D865 2010
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