ISBN-10:
0471007102
ISBN-13:
9780471007104
Pub. Date:
05/28/1995
Publisher:
Wiley
Probability and Measure / Edition 3

Probability and Measure / Edition 3

by Patrick Billingsley

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Overview

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.

Product Details

ISBN-13: 9780471007104
Publisher: Wiley
Publication date: 05/28/1995
Series: Wiley Series in Probability and Statistics Series , #245
Edition description: REV
Pages: 608
Product dimensions: 6.48(w) x 9.41(h) x 1.37(d)

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.

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Table of Contents

Probability.

Measure.

Integration.

Random Variables and Expected Values.

Convergence of Distributions.

Derivatives and Conditional Probability.

Stochastic Processes.

Appendix.

Notes on the Problems.

Bibliography.

List of Symbols.

Index.

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