Probability and Measure

Wiley Series in Probability and Mathematical Statistics

by Patrick Billingsley

Praise for the Third Edition "It is, as far as I'm concerned, among the best books in math ever written....if you are a mathematician and want to have the top reference in probability, this is it." (Amazon.com, January 2006) A complete and comprehensive classic in probability and measure theory Probability and Measure, Anniversary Edition by Patrick Billingsley celebrates the achievements and advancements that have made this book a classic in its field for the past 35 years. Now re-issued in a new style and format, but with the reliable content that the third edition was revered for, this Anniversary Edition builds on its strong foundation of measure theory and probability with Billingsley's unique writing style. In recognition of 35 years of publication, impacting tens of thousands of readers, this Anniversary Edition has been completely redesigned in a new, open and user-friendly way in order to appeal to university-level students. This book adds a new foreward by Steve Lally of the Statistics Department at The University of Chicago in order to underscore the many years of successful publication and world-wide popularity and emphasize the educational value of this book. The Anniversary Edition contains features Patrick Billingsley was a first-class, world-renowned authority in probability and measure theory at a leading U.S. institution of higher education. He continued to be an influential probability theorist until his unfortunate death in 2011. Billingsley earned his Bachelor's Degree in Engineering from the U.S. Naval Academy where he served as an officer. he went on to receive his Master's Degree and doctorate in Mathematics from Princeton University.Among his many professional awards was the Mathematical Association of America's Lester R. Ford Award for mathematical exposition. His achievements through his long and esteemed career have solidified Patrick Billingsley's place as a leading authority in the field and been a large reason for his books being regarded as classics. This Anniversary Edition of Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Like the previous editions, this Anniversary Edition is a key resource for students of mathematics, statistics, economics, and a wide variety of disciplines that require a solid understanding of probability theory.

Genres: Mathematics, Textbooks, Nonfiction

656 pages, Hardcover

First published January 1, 1979

Reviews

[Nour · Rating 3 out of 5]

in the general probability is somthing hard to understand , other thing the book was hard to read it , but it is interesting

[Tinwerume · Rating 4 out of 5]

Overall I'm quite happy with it, although then again I am comparing against Kallenberg so maybe my baseline is just skewed.

I also only read chapters 5 and 6 (convergence and conditionals), although I'd be surprised if earlier chapters were worse given the relatively easier material.

[Javier Burroni · Rating 5 out of 5]

Almost any book on formal probability ends up referring to this book at some point.
Therefore, it’s better to just begin with this one.
It is worth to mention that it’s contained

[Edith Z · Rating 5 out of 5]

Both concise and understandable (rare combination), really good examples, exercises were a bit challenging

[W · Rating 5 out of 5]

all-time classic, doesn't need the recommendation

[Chase Abram · Rating 3 out of 5]

This is fine. Elegance was clearly not a priority in the proofs, and I found many of the exercises more frustrating than illustrative.

[Steven Knox · Rating 2 out of 5]

This book succeeds at its apparent goal: be a single, self-contained work on measure-theoretic probability. Having worked through Billingsley's book, if someone asked me how to learn measure-theoretic probability my answer would be to work through a book on measure theory (say, Royden's Real Analysis) without probability, and then read Kolmogorov's seminal work Foundations of the Theory of Probability which applies measure theory to probability.

[Jerzy]

Browsing through, this seems fairly well-written -- but I should wait until I've picked up some more background in real analyis.

[Elmansouri]

i want to read it

[Mtaboga · Rating 4 out of 5]

Not an easy read, but contains many interesting results not found elswhere.