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Probability with R: An Introduction with Computer Science Applications



Description:

A Complete Introduction to probability AND its computer ScienceApplications USING R

Probability with R serves as a comprehensive andintroductory book on probability with an emphasis oncomputing-related applications. Real examples show how probabilitycan be used in practical situations, and the freely available anddownloadable statistical programming language R illustrates andclarifies the book's main principles.

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

  • The R Language presents the essentials of the R language,including key procedures for summarizing and building graphicaldisplays of statistical data.

  • Fundamentals of Probability provides the foundations ofthe basic concepts of probability and moves into applications incomputing. Topical coverage includes conditional probability,Bayes' theorem, system reliability, and the development of the mainlaws and properties of probability.

  • Discrete Distributions addresses discrete randomvariables and their density and distribution functions as well asthe properties of expectation. The geometric, binomial,hypergeometric, and Poisson distributions are also discussed andused to develop sampling inspection schemes.

  • Continuous Distributions introduces continuous variablesby examining the waiting time between Poisson occurrences. Theexponential distribution and its applications to reliability areinvestigated, and the Markov property is illustrated via simulationin R. The normal distribution is examined and applied tostatistical process control.

  • Tailing Off delves into the use of Markov and Chebyshevinequalities as tools for estimating tail probabilities withlimited 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 calculationsand conduct experiments with simulated data. The author directsreaders to the appropriate Web-based resources for installing the Rsoftware package and also supplies the essential commands forworking in the R workspace. A related Web site features an activeappendix as well as a forum for readers to share findings,thoughts, and ideas.

With its accessible and hands-on approach, Probability withR is an ideal book for a first course in probability at theupper-undergraduate and graduate levels for readers with abackground in computer science, engineering, and the generalsciences. It also serves as a valuable reference for computingprofessionals who would like to further understand the relevance ofprobability in their areas of practice.

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