An intuitive, yet precise introduction to probability theory, stochastic
processes, and probabilistic models used in science, engineering, economics,
and related fields. The 2nd edition is a substantial revision of
the 1st edition, involving a reorganization of old material and the addition
of new material. The length of the book has increased by about 25 percent.
The main new feature of the 2nd edition is thorough introduction to Bayesian
and classical statistics.

The book is the currently used textbook for "Probabilistic Systems Analysis,"
an introductory probability course at the Massachusetts Institute of Technology,
attended by a large number of undergraduate and graduate students. Covers the
fundamentals of probability theory (probabilistic models, discrete and continuous
random variables, multiple random variables, and limit theorems), which are
typically part of a first course on the subject, as well as the fundamental
concepts and methods of statistical inference, both Bayesian and classical.
It also contains, a number of more advanced topics, from which an instructor
can choose to match the goals of a particular course. Topics include transforms,
sums of random variables, a fairly detailed introduction to Bernoulli, Poisson,
and Markov processes.

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