An introduction to probability at the undergraduate level
Chance and randomness are encountered on a daily basis. Authored
by a highly qualified professor in the field, Probability: With
Applications and R delves into the theories and applications
essential to obtaining a thorough understanding of probability.
With real-life examples and thoughtful exercises from fields as
diverse as biology, computer science, cryptology, ecology, public
health, and sports, the book is accessible for a variety of
readers. The book’s emphasis on simulation through the use of
the popular R software language clarifies and illustrates key
computational and theoretical results.
Probability: With Applications and R helps readers
develop problem-solving skills and delivers an appropriate mix of
theory and application. The book includes:
* Chapters covering first principles, conditional probability,
independent trials, random variables, discrete distributions,
continuous probability, continuous distributions, conditional
distribution, and limits
* An early introduction to random variables and Monte Carlo
simulation and an emphasis on conditional probability,
conditioning, and developing probabilistic intuition
* An R tutorial with example script files
* Many classic and historical problems of probability as well as
nontraditional material, such as Benford’s law, power-law
distributions, and Bayesian statistics
* A topics section with suitable material for projects and
explorations, such as random walk on graphs, Markov chains, and
Markov chain Monte Carlo
* Chapter-by-chapter summaries and hundreds of practical
exercises
Probability: With Applications and R is an ideal text for
a beginning course in probability at the undergraduate level.

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