Book review: Statistical Analysis with R

The programming language R is a standard for statisticians. And it is free software which runs on Windows, Mac and Linux.

You can learn much online about R, but if you prefer a bona fide book, there are also many to choose from. I just finished one of those: Statistical Analysis with R by John M. Quick.

The book is colorful and ludic which is a good idea for a “Beginner’s Guide”. The layout is attractive, there are many detailed examples. I like the pedagogy: the author wants you to learn by doing. However, the book is poor as a reference: the coverage is limited despite the 300 pages and the chapter summaries are strictly non-technical.

Overall this is a good book for people with no programming background who just want to use R to load data, do ANOVA tests and simple models. They will find step-by-step instructions down to the installation of the software, complete with screenshots of every step. This could be a good book for scientists or business people who want to try R as a substitute for Excel.

Disclosure: I got a free copy of the e-book from the publisher with the expectation that I would publish a review.

Published by

Daniel Lemire

A computer science professor at the University of Quebec (TELUQ).

One thought on “Book review: Statistical Analysis with R”

  1. While not yet release the Manning book R in action (available in the MEAP program) is not only a good beginner guide, but is very well organized and provides education on statistical methods for those not versed in the subject. A very good book for programmers with decent Math education, but not enough statistics courses under their belts…

    I would say that it is not a great “reference” but it points you at the right set of starting packages in a task oriented way.

    Reply

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