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Getting Started With R |
The R programming language is the most advanced statistical computing environment available. Anyone wishing to: use state of the art statistical packages, produce state of the art statistical graphics, or have a flexibile computing environment in which to develop state of the art statistical software will want to use R.
Here are some R resources:
(1) An overview of the R programming language is provided at The R Project for Statistical Computing.
(2) Download R from The Comprehensive R Archive Network (CRAN). Versions are available for Linux, Mac OSX, and Windows in both 32-bit and 64-bit installations.
(3) R comes with a default GUI. However if you would like to have a nicer interface that is more like an IDE, then try RStudio. Note that RStudio requires that you already have R installed.
R for Everyone by Lander This book is a basic introduction to R for the R beginner. It provides a basic understaning of working with data in R, programming with R, and an overview of several useful R packages and how they are used. |
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The R Book by Michael J. Crawley This book is a massive (~1000 pages) comprehensive reference to help you perform the most common statistical analyses. The book is a must have for the beginner who wishes to become a sophisticated R user. |
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Data Mining and Business Analytics with R by Johanes Ledolter This book is a nice self contained instroduction to a broad spectrum of analytical techniques from statistics and machine learning by example in R. This book would be a very good starting point for learning about the different modeling capabilities of R. |
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Data Manipulation with R by Phil Spector This book is a must have for the industry R user. As the title suggests the book focuses on data manipulation in R, including interacting with a SQL data base using R, manipulating dates and strings in R, and rehaping data in R. |
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A Modern Approach to Regression with R by Simon Sheather If you want to begin to understand how statistician's are trained to think about statistical modeling through the entire modeling process: explorartory data analysis, model building, and assessment of the model goodness-of-fit, then you will need a modeling book based on R. You should note that R is developed and maintained by research statisticians, hence it is the only statistical software that is developed with the tools to develop statistical models from a statistical point of view. Note that the book itself does not contain R code. For data sets and R code see the book web site: www.stat.tamu.edu/~sheather/book. |
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Linear Models with R by Julian J. Faraway This book is a very task oriented modeling book. In this book Faraway illustrates how to perform each step of a regression analysis in R with direct reference to specific R code within the context of an example. The book is very light on the underlying statistical concepts, but very heavy on the R implementation. Typically this book works very well in conjunction with another text such as Sheather's book. |
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Applied Regression Analysis and Generalized Linear Models by John Fox This book provides a thorough introduction to Ordinary Least Squares regression analysis and some more advanced topics from Generalized Lienar Models and Robust Regression. The book is written at the same level as Sheather. |
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Modern Regression Techniques Using R by Wright and London Nice introduction to the more advanced topics in regression models with a focus on using these methods in R. |
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ggplot2: Elegant Graphics for Data Analysis by Hadley Wickham R is capable of producing very sophisticated statistical graphics. However, producing these graphics takes an understanding of how R builds the components of a plot and how to reference and define those parameters. The easiest way for the beginner to produce high quality graphics is to use the ggplot2 graphics package. |
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Lattice: Multivariate Data Visualization with R by Deepayan Sarkar The Lattice package can be used to simplify the production of views of multivariate data using a functional notation and without the need to subset your data frame. The package can be extremely useful if you like to use statistical graphics in your Exploratory Data Analysis. |
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Software for Data Analysis: Programming with R by John Chambers When you have reached the point that you understand the basics of R and you have decided that you want to become a very serious R programmer, then this is the book for you. R is a derivative of the S Programming Language, winner of the 1998 ACM Software System Award, which was created at Bell Laboratories by John Chambers. The books on S (and R) written by Chambers are considered to be definitive sources on the R programming language. |
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R Graphics by Paul Murrell If you want to be able to develop your own sophisticated R graphics from scratch, then you will need to read and understand this book. This book outlines the building blocks of a R plot and how to modify those building blocks. |