Probability and Measure (Wiley Series in Probability and Statistics)

A senior-graduate level text and reference that links the disciplines of probability and measure theory. Including many practical problems and examples, it begins with an introduction to Borel's normal number theorem, proved by calculus alone, followed by short sections that establish the existence and fundamental properties of probability measures, including Lebesque measure on the unit interval. Coverage includes topics in measure, integration, random variables and expected values, convergence of distributions, derivatives and conditional probability, and stochastic processes.

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.