Data analysis and statistical computing have become important due to their numerous and ever-increasing applications in business and other areas. R is a widely used programming language suitable for applications involving statistics, data analysis, and data mining. It is an open-source project of GNU and is freely available for various operating systems under the GNU general public license. A number of books deal with various aspects and applications of R (see, for example, those listed in [1]). This book is meant to be a quick syntax reference book for R. It is available in e-book as well as print formats, and is intended for statisticians, data analysts, and data scientists.

The book is made up of six parts. Part 1 describes how to download and install R for operating systems such as Windows, Mac, and Linux. It also discusses how to download packages and how to update R. Graphical user interface (GUI)-based versions of R are available; nonetheless, the focus of this book is on using R through a command prompt.

In Part 2, the author focuses on the object-oriented programming aspects of R by describing R objects. The modes, classes, and types of objects are described here. Some of the functions available in R are covered in Part 3. Some of the default packages in R are listed, along with hints on how to use the functions in those packages.

Part 4 focuses on mechanisms for exporting data from R and also importing data into it. There is also some discussion about some random-number generators and functions that operate on objects. Commands and functions for controlling flow are examined in Part 5. Functions and statements for conditioning flow are given, along with suitable examples.

Part 6 focuses on formatting and functions related to it. It also looks at structuring output. Some tips are also given for overcoming some of the common frustrations in R.

The book is well written in a manner suitable for its intended audience. Although many books on R are available, this book tends to concentrate on the essentials needed for using R. The author has done a good job by producing a handy and compact quick reference for the ever-growing and popular statistical programming language R. This book compares well with similar books [2] and is very reasonably priced. I strongly recommend the print as well as e-book versions for enthusiasts of statistical computing and data analysis.

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