Click Here To Purchase The R Book 

Author: Michael Crawley
Publisher: Wiley
ISBN: 0470510242

R is an open source statistical package, supported by a wide range of add on packages written by the user community for an array of statistical analysis.

The R Book by Michael Crawley is a very useful book in making accessible the wide functionality available to users, highlighting the most important functions in the R language and packages. The book is not just a guidebook to R, but touches upon many aspects of statistical data analysis in general.

Although there are hundreds of R packages available, which provide a wide range of statistical functionality, the book has provided a concentrated but extensive list of functions and statistical methods which appeal to a broad range of people doing statistical analysis in different fields.

Only a introductory level of statistics is assumed in the whole book. The book starts with downloading the software, installation, ensuring that the required packages are installed, and other basics such as using the editor and changing the look and feel.

The foundation of the book is the chapter on Essentials of the language which is a comprehensive account of the features of the R language which documents important built in functions as well as handling special situations like missing values and non numeric values in data.

The book does not just documents the language functionality, but describes aspects of handling data for doing statistical analysis. Basic features of a programming language such as operators, vector functions, subscripts are described. Good practices for R usage in handling data are given.

Matrices and functions related to matrices are given due importance. Statistical examples like the variance ratio test are used to demonstrate writing functions in R, while touching upon good programming practices such as avoiding loops. Functionality such as pattern matching, and date and time functions are covered.

Data input covers key functionality of scanning data from files and excel sheets. The book addresses common problems users encounter, apart from the different ways of reading lines from a file and how to organize and manipulate data in data frames.

R has a very sophisticated graphics capability. The author describe the key graph types available including the two-variable, single sample, multivariate and special plots. Also, each chapter highlights the graphics functionality further by generating the output of the analysis in a plot that is most suitable for presentation purposes. Almost all types of graphs are covered.

Mathematical functions are comprehensively covered in the book, including a list of continuous and discrete random variables. Key functionality in handling matrix algebra, calculus, and ordinary differential equations are given. The book also provides sufficient background detail to get started in using these functions.

The chapter on statistical modeling highlights ways to choose an appropriate statistical method, different types of statistical models, steps for model simplification, model implementation in R, and checking the efficiency of the model. Classical tests for testing normality, quantifying non normality, comparing variances, means, paired samples, etc are dealt with in good detail.

The book covers a host of regression techniques in detail including linear, piecewise, robust, multiple, non linear, and non parametric regressions. While describing the analysis of variance and covariance, the book describes not just the statistical technique and its syntax in R, but also reasons for using the technique, when is it used, handling of special cases, and appropriate graphing facilities in R.

In the chapter on Generalized Linear Models, the book not only explains why the technique is used, it also explains the key concept of a link function very clearly and touches upon important issues such as measuring goodness of fit of a GLM and bootstrapping with GLM. Thus the book is not just a cook book of R functions, but strives to provide insight into using R from all aspects of using a statistical technique.

The book will not only have great appeal to newbies to the R language but also be a great reference to experienced R users as the book covers almost all the important functionality of R and touches upon the required background to use these functions intelligently.

Click Here To Purchase The R Book

The above review was contributed by: Manoj Rengarajan:  Manoj holds a Master of Financial Engineering - University of California, Berkeley and he works in the investment management industry and specializes in providing economic and investment outlook andstrategy for global equityand government bond markets. He has an educational background in financialengineering, business, and engineering, and professional interests include business, finance, economics, technology and related areas. To read Manoj's reviews CLICK HERE