Probability : With Applications and R

Robert P. Dobrow

ISBN 10: 1118241258 / ISBN 13: 9781118241257

Published by Wiley & Sons, 2013

About this Item

Neuware - An introduction to probability at the undergraduate levelChance 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 exercisesProbability: With Applications and R is an ideal text for a beginning course in probability at the undergraduate level.

Seller Inventory # 9781118241257

Bibliographic Details

• Title: Probability : With Applications and R
• Publisher: Wiley & Sons
• Publication Date: 2013
• Language: English
• ISBN 10: 1118241258
• ISBN 13: 9781118241257
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 150H x 38D millimeters 250 millimeters width by 150 millimeters height by 38 millimeters depth
• Weight: 938 grams

About this title

Synopsis

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.

About the Author

ROBERT P. DOBROW, PhD, is Professor of Mathematics at Carleton College. He has taught probability for over fifteen years and has authored numerous papers in probability theory, Markov chains, and statistics.