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 limitsAn
early introduction to random variables and Monte Carlo simulation
and an emphasis on conditional probability, conditioning, and
developing probabilistic intuitionAn R tutorial with example script
filesMany classic and historical problems of probability as well as
nontraditional material, such as Benford's law, power-law
distributions, and Bayesian statisticsA topics section with
suitable material for projects and explorations, such as random
walk on graphs, Markov chains, and Markov chain Monte
CarloChapter-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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