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.
An edition of Probability and Measure
(1979)
Probability and Measure
3rd ed.
by Patrick Billingsley
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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.
--back cover
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Probabilities, Measure theory, Qa273 .b575 1995, 519.2Showing 7 featured editions. View all 7 editions?
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Probability and Measure
1995, Wiley-Interscience
Hardcover
in English
- 3rd ed.
0471007102 9780471007104
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Includes bibliographical references (p. 581-583) and index.
"A Wiley-Interscience publication."
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