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Probability and Measure, 3rd Edition [Hardcover]

Patrick Billingsley (Author)
3.9 out of 5 stars  See all reviews (13 customer reviews)

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Book Description

0471007102 978-0471007104 April 17, 1995 3
PROBABILITY AND MEASURE

Third Edition

Now in its new third edition, Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Retaining the unique approach of the previous editions, this text interweaves material on probability and measure, so that probability problems generate an interest in measure theory and measure theory is then developed and applied to probability. Probability and Measure provides thorough coverage of probability, measure, integration, random variables and expected values, convergence of distributions, derivatives and conditional probability, and stochastic processes. The Third Edition features an improved treatment of Brownian motion and the replacement of queuing theory with ergodic theory.

Like the previous editions, this new edition will be well received by students of mathematics, statistics, economics, and a wide variety of disciplines that require a solid understanding of probability theory.

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Editorial Reviews

From the Back Cover

PROBABILITY AND MEASURE

Third Edition

Now in its new third edition, Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Retaining the unique approach of the previous editions, this text interweaves material on probability and measure, so that probability problems generate an interest in measure theory and measure theory is then developed and applied to probability. Probability and Measure provides thorough coverage of probability, measure, integration, random variables and expected values, convergence of distributions, derivatives and conditional probability, and stochastic processes. The Third Edition features an improved treatment of Brownian motion and the replacement of queuing theory with ergodic theory.

Like the previous editions, this new edition will be well received by students of mathematics, statistics, economics, and a wide variety of disciplines that require a solid understanding of probability theory.

About the Author

PATRICK BILLINGSLEY is Professor of Statistics and Mathematics at the University of Chicago. He is the coauthor (with Watson et al.) of Statistics for Management and Economics; (with D. L. Huntsberger) of Elements of Statistical Inference; and the author of Convergence of Probability Measures (Wiley-Interscience), among other works. Dr. Billingsley has also edited the Annals of Probability for the Institute of Mathematical Statistics. He received his PhD in mathematics from Princeton University.

Product Details

  • Hardcover: 608 pages
  • Publisher: Wiley-Interscience; 3 edition (April 17, 1995)
  • Language: English
  • ISBN-10: 0471007102
  • ISBN-13: 978-0471007104
  • Product Dimensions: 9.6 x 6.4 x 1.4 inches
  • Shipping Weight: 2.1 pounds (View shipping rates and policies)
  • Average Customer Review: 3.9 out of 5 stars  See all reviews (13 customer reviews)
  • Amazon Best Sellers Rank: #330,454 in Books (See Top 100 in Books)

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Customer Reviews

13 Reviews
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Average Customer Review
3.9 out of 5 stars (13 customer reviews)
 
 
 
 
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30 of 31 people found the following review helpful:
5.0 out of 5 stars An exceptionally good book, December 19, 2006
This review is from: Probability and Measure, 3rd Edition (Hardcover)
I've read portions of almost every measure theoretic probability theory book published. And I've come back to Billingsley. This is a hard book to read through and through if you are a novice; this is not Billingsley's fault - it is just that the subject is hard on first acquaintance.
Billinglsey develops everything from first principles, so if you have the intellectual gumption you ought to be able to read the main text with a knowledge of plain college algebra and a little epsilon-delta practice of the sort that comes from an undergraduate real analysis course. The small print asides are fascinating but they are often addressed to a card carrying mathematician. The November 2003 reviewer who complained that Billingsley uses expectation before defining the integral fails to notice - or at any rate, to point out - that he defines only the expectation of simple random variables in the first chapter, so what is involved is just a sum, not an integral. I could sing my praises on and on. But here is the kernel of this review in a line: this is one of the best books ever written on measure theoretic probability. Full stop.
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30 of 33 people found the following review helpful:
5.0 out of 5 stars Excellent introduction and reference., January 12, 1999
By A Customer
This review is from: Probability and Measure, 3rd Edition (Hardcover)
This book is a thorough introduction and excellent reference book for the ideas involving probability as a measure. I would recommend this book to anyone who needs a deep understanding of probability, expectation, integration, random variables, and so forth. Good also as a graduate level or other measure-theoretic probability course. Two years after I learned these ideas, I still refer often to the text.
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24 of 27 people found the following review helpful:
3.0 out of 5 stars Probability Theory Bible, September 1, 2001
By 
Stanislav Kolenikov (Columbia, MO, United States; Moscow, Russia) - See all my reviews
(REAL NAME)   
This review is from: Probability and Measure, 3rd Edition (Hardcover)
"Probability and Measure" by P. Billingsley covers a lot of topics in probability theory, and in this sense it is a standard reference, but what I did not like much is that the concepts are somewhat scattered around the book, so one has to jump back and forth all the time. (May be this is an artefact of my graduate course in probability theory that had topics in the syllabus ordered in a way different from Billingsley.) I found another book more useful and more clearly written -- see Borovkov et. al. Probability Theory (I cannot believe it is so overpriced though!!!!)
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Inside This Book (learn more)
First Sentence:
Although sufficient for the development of many interesting topics in mathematical probability, the theory of discrete probability spaces does not go far enough for the rigorous treatment of problems of two kinds: those involving an infinitely repeated operation, as an infinite sequence of tosses of a coin, and those involving an infinitely fine operation, as the random drawing of a point from a segment. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
cocountable sets, subfair case, normal number theorem, field moo, negligible complement, simple random variables, centered normal distribution, separable with respect, fixed discontinuities, nth play, finitely additive probability measure, cofinite sets, trifling set, martingale relative, nonnegative case, countable subadditivity, infinite capital, irreducible solutions, measurable rectangles, sum extending, dyadic expansion, bold play, unit stakes, aperiodic chain, initial fortune
Key Phrases - Capitalized Phrases (CAPs): (learn more)
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