Probability with R (eBook)

A Complete Introduction to probability AND its computer Science
Applications USING R

Probability with R serves as a comprehensive and
introductory book on probability with an emphasis on
computing-related applications. Real examples show how probability
can be used in practical situations, and the freely available and
downloadable statistical programming language R illustrates and
clarifies the book's main principles.

Promoting a simulation- and experimentation-driven methodology,
this book highlights the relationship between probability and
computing in five distinctive parts:

* The R Language presents the essentials of the R language,
including key procedures for summarizing and building graphical
displays of statistical data.

* Fundamentals of Probability provides the foundations of
the basic concepts of probability and moves into applications in
computing. Topical coverage includes conditional probability,
Bayes' theorem, system reliability, and the development of the main
laws and properties of probability.

* Discrete Distributions addresses discrete random
variables and their density and distribution functions as well as
the properties of expectation. The geometric, binomial,
hypergeometric, and Poisson distributions are also discussed and
used to develop sampling inspection schemes.

* Continuous Distributions introduces continuous variables
by examining the waiting time between Poisson occurrences. The
exponential distribution and its applications to reliability are
investigated, and the Markov property is illustrated via simulation
in R. The normal distribution is examined and applied to
statistical process control.

* Tailing Off delves into the use of Markov and Chebyshev
inequalities as tools for estimating tail probabilities with
limited information on the random variable.

Numerous exercises and projects are provided in each chapter,
many of which require the use of R to perform routine calculations
and conduct experiments with simulated data. The author directs
readers to the appropriate Web-based resources for installing the R
software package and also supplies the essential commands for
working in the R workspace. A related Web site features an active
appendix as well as a forum for readers to share findings,
thoughts, and ideas.

With its accessible and hands-on approach, Probability with
R is an ideal book for a first course in probability at the
upper-undergraduate and graduate levels for readers with a
background in computer science, engineering, and the general
sciences. It also serves as a valuable reference for computing
professionals who would like to further understand the relevance of
probability in their areas of practice.