An introduction to probability at the undergraduate level
Chance and randomness are encountered on a daily basis. Authoredby a highly qualified professor in the field, Probability: WithApplications and R delves into the theories and applicationsessential to obtaining a thorough understanding of probability.
With real-life examples and thoughtful exercises from fields asdiverse as biology, computer science, cryptology, ecology, publichealth, and sports, the book is accessible for a variety ofreaders. The book's emphasis on simulation through the use ofthe popular R software language clarifies and illustrates keycomputational and theoretical results.
Probability: With Applications and R helps readersdevelop problem-solving skills and delivers an appropriate mix oftheory and application. The book includes:
* Chapters covering first principles, conditional probability,independent trials, random variables, discrete distributions,continuous probability, continuous distributions, conditionaldistribution, and limits
* An early introduction to random variables and Monte Carlosimulation 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 asnontraditional material, such as Benford's law, power-lawdistributions, and Bayesian statistics
* A topics section with suitable material for projects andexplorations, such as random walk on graphs, Markov chains, andMarkov chain Monte Carlo
* Chapter-by-chapter summaries and hundreds of practicalexercises
Probability: With Applications and R is an ideal text fora beginning course in probability at the undergraduate level.