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The book of R : a first course in programming and statistics
Davies T., No Starch Press, San Francisco, CA, 2015. 432 pp. Type: Book (978-1-593276-51-5)
Date Reviewed: Oct 6 2016

A recent survey by O’Reilly Media [1] finds the R language [2] among the top big data analysis tools, along with SQL. Interest in this open-source software project has increased dramatically as organizations learn to exploit the ever-increasing size and variety of data they collect.

The book of R is more than a textbook on one of the most widely used statistical packages for data analytics; it is also a brief yet reasonably comprehensive introduction to basic statistics. The author teaches that subject using R, and the book reflects the tutorial style and content of an instructional resource. Somewhat surprisingly, this 750-plus-page tome was derived from the author’s three-day workshops on R and statistics, and covers basic through advanced R programming examples, including 3D graphics output. Along the way, Davies interleaves statistical concepts and methodology instruction, covering descriptive statistics, visualization, sampling and hypothesis testing, ANOVA, and simple and multiple regression. It is quite ambitious, yet suitable for readers with at least some mathematical and programming background and experience.

The book’s appendix covers installation of R on Windows, Linux, and Apple systems, and includes brief discussions of the myriad custom add-on dataset and software packages for R, such as clinical trial design, ecological and environmental data, and natural language processing. And for those who prefer a graphical rather than command-line R interface, another appendix covers the RStudio programming environment.

Each section includes a collection of illustrative exercises, some of which can be quite challenging. Thus, the book could serve as a primary textbook for an introductory statistics course, although that should be supplemented with a more thorough textbook on statistical theory and practice, as well as additional background on data visualization.

Overall, The book of R is an excellent reference for novice data analysts and for students being introduced to statistical programming tools. The author’s website (https://www.nostarch.com/bookofr) provides downloads of the book’s example source code, exercise solutions, and sample color plots and visualizations.

More reviews about this item: Amazon

Reviewer:  Harry J. Foxwell Review #: CR144818 (1701-0008)
1) King, J.; Magoulas, R. 2015 data science salary survey. O'Reilly, Sept. 23, 2015. https://www.oreilly.com/ideas/2015-data-science-salary-survey.
2) The comprehensive R archive network, https://cran.r-project.org/. Accessed 10/4/15.
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