By John M Quick

The R Tutorial Series provides a collection of user-friendly tutorials to people who want to learn how to use R for statistical analysis.

My Statistical Analysis with R book is available from Packt Publishing and Amazon.

R Beginner's Guide Book Update: Statistical Analysis with R Released

In the final days of October, my beginner's guide to R was released. The book's official title is Statistical Analysis with R and it can be found on the Packt Publishing website.
The primary focus of Statistical Analysis with R is helping new users become accustomed to R and empowering them to apply R to suit their own needs. No prior experience with R, statistical software packages, or programming is necessary to learn from this book. It is written for a broad audience and should be well received by businesspeople, IT professionals, researchers, and students alike. Statistical Analysis with R takes readers on a journey from their first installation and launch of R, to analyzing and assessing data, to communicating and visualizing results. This guide is an excellent way to rapidly become an experienced R user and learn the skills that you need to apply R to your work.


A sample chapter from Statistical Analysis with R is available from the Packt website. This chapter, the book's eight, introduces the graphical capabilities of R, such as generating, customizing, and exporting various plots, charts, and graphs. You can download the sample chapter and its accompanying R files for free. If you like this chapter and are interested in learning more about R's graphical capabilities, you should know that chapter 9 demonstrates in depth how you can build and customize your own R visualizations.
The publisher has also posted a few brief samples from the book, which can be accessed via the following links. These samples are taken from chapters 7 and 8 of Statistical Analysis with R. Respectively, they cover the common process behind all R analyses and introduce the graphical capabilities of R.


If you decide to read Statistical Analysis with R, please feel free to provide me with your feedback. It would be great to know what you learned from the book, how future guides could be improved, and your overall experience with R.