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Book Description
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Why learn R? Because it's rapidly becoming the standard for developing statistical software. R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics.
The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems.
- Understand the basics of the language, including the nature of R objects
- Learn how to write R functions and build your own packages
- Work with data through visualization, statistical analysis, and other methods
- Explore the wealth of packages contributed by the R community
- Become familiar with the lattice graphics package for high-level data visualization
- Learn about bioinformatics packages provided by Bioconductor
"I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians."
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Customer Reviews
Unfortunately the book's organisation both at the level of ideas and of navigation leaves it sorely lacking as both a tutorial and as a reference.
Coverage of the language is patchy and the index makes finding even those subjects that are covered in the text difficult.
The structure is slightly contrived with the topics forced into a "Problem - Solution - Discussion" treatment but the cross-referencing is well done and examples are given which are easy to transfer into R.
There are lots of topics presented here that I have found quite difficult to get by searching the help archives (including a good guide to finding help) but particularly in data transformation and applying functions.
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