Decoupling theory provides a general framework for analyzing problems
involving dependent random variables as if they were independent. It was
born in the early 1980s as a natural continuation of martingale theory
and has acquired a life of its own due to vigorous development and wide
applicability. The authors provide a friendly and systematic
introduction to the theory and applications of decoupling. This book is
addressed to researchers and graduate students in probability and
statistics. The exposition is at the level of a second graduate
probability course, with a good portion of the material fit for use in a
first year course.