Probability and Measure

This Anniversary Edition of Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Retaining intact the unique approach of the Third Edition, this text interweaves material on probability and measure, so that probability problems generate an interest in measure theory, which 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, stochastic processes, Brownian motion, and ergodic theory. The Anniversary Edition features a new, pedagogically sound interior design with an emphasis on open space.Like the previous editions, this Anniversary 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.

Keywords: Probability & Mathematical Statistics, Probability, measure theory, integration, random variables, expected values, convergence of distributions, derivatives and conditional probability, stochastic processes, Brownian motion