Sunday, February 27, 2022

Review of "A First Course in Statistical Programming With R," by W. John Braun and Duncan J. Murdoch

 Review of

 A First Course in Statistical Programming With R, by W. John Braun and Duncan J. Murdoch, Cambridge University Press, New York, NY, 2008. 163 pp., $50.00 (paper). ISBN 978-0-521-69424-7.

  R is a package that allows the user to use pre-existing packages to perform some mathematical operations. It is very easy to install and use with a user window that is very similar in appearance to that of MapleÓ and MathematicaÓ.

 However, even the most intuitive of packages still presents some points of confusion, but with this book, you can be up and running, doing very advanced work with R in a matter of minutes. Using a series of code examples, the authors take you through many of the basic capabilities of the package. All that is needed to follow the examples is a basic understanding of control constructs such as the if-then, loops and functions as well as knowledge of the underlying mathematics.

Areas of mathematics that are supported by the basic R package include:


*) Statistical graphics

*) Computational linear algebra

*) Monte Carlo simulations using several different random number distributions such as the Poisson distribution

*) Numerical optimization

*) Linear programming


Windows versions also allow you to set the locale so that languages other than English can be used.

 While it is rare to see in a book, denseness does not have to be difficult, and this book is an example of that. The authors are terse and effective as they clearly demonstrate how to use the R package.  If you lack the budget for the purchase of a commercial computational mathematics package, then R with this textbook provides a very low cost alternative for many classes.

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