Focusing on developing practical R skills rather than teaching pure statistics, Dr. Kurt Taylor Gaubatz's A Survivor's Guide to R provides a gentle yet thorough introduction to R. The book is structured around critical R tasks, and focuses on applied knowledge, rather than abstract concepts. Gaubatz's easy-to-read approach helps students with little or no background in statistics or programming to develop real-world R skills through straightforward coverage of R objects and functions. Focusing on real-world data, the challenges of dataset construction, and the use of R's powerful graphing tools, the guide is written in an accessible, sympathetic, even humorous style that ensures students acquire functional R skills they can use in their own projects and carry into their work beyond the classroom.
As the world becomes Increasingly digital, there are growing amounts of easily available textual data that can be used for all manner of analytic issues. It is also often the case that we have numeric data that are locked up in textual formats: for example, the output of other statistics programs, data lists in textual form or data tables from published sources.
As we have seen, R can deal with textual variables. It is not the most elegant or efficient program for this realm,1 but as long as you are already learning R and using it for your statistical analysis, it is often the path of least resistance to incorporate text processing into your R work....