An essential guide to the concepts of probability theory that puts the
focus on models and applications
Introduction to Probability offers an authoritative text that presents
the main ideas and concepts, as well as the theoretical background,
models, and applications of probability. The authors--noted experts in
the field--include a review of problems where probabilistic models
naturally arise, and discuss the methodology to tackle these problems.
A wide-range of topics are covered that include the concepts of
probability and conditional probability, univariate discrete
distributions, univariate continuous distributions, along with a
detailed presentation of the most important probability distributions
used in practice, with their main properties and applications.
Designed as a useful guide, the text contains theory of probability, de
finitions, charts, examples with solutions, illustrations,
self-assessment exercises, computational exercises, problems and a
glossary. This important text:
- Includes classroom-tested problems and solutions to probability
exercises
- Highlights real-world exercises designed to make clear the concepts
presented
- Uses Mathematica software to illustrate the text's computer
exercises
- Features applications representing worldwide situations and
processes
- Offers two types of self-assessment exercises at the end of each
chapter, so that students may review the material in that chapter and
monitor their progress.
Written for students majoring in statistics, engineering, operations
research, computer science, physics, and mathematics, Introduction to
Probability: Models and Applications is an accessible text that explores
the basic concepts of probability and includes detailed information on
models and applications.
