R is a programming language and free software environment for statistical computing and graphics. It compiles and runs on UNIX platforms, Windows and Mac Operating System.
Interestingly, R was created by Ross Ihaka and Robert Gentleman at the University of Auckland. It is named after the first names of its creator.
There are more than 70 titles on R programming language at Unitec Library, mostly are electronic books - see here
Selected books/ebooks are listed below:
Statistics for People Who (Think They) Hate Statistics Using R by
Neil J. Salkind's bestselling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an often intimidating subject since it first published in 2000. Now the bestselling SPSS® and Excel® versions are joined by a text for use with the R software, Statistics for People Who (Think They) Hate Statistics Using R. New co-author Leslie A. Shaw carries forward Salkind's signature humorous, personable, and informative approach as the text guides students in a grounding of statistical basics and R computing, and the application of statistics to research studies. The book covers various basic and advanced statistical procedures, from correlation and graph creation to analysis of variance, regression, non-parametric tests, and more.
Beginning R by
Gain better insight into your data using the power of R While R is very flexible and powerful, it is unlike most of thecomputer programs you have used. In order to unlock its fullpotential, this book delves into the language, making it accessibleso you can tackle even the most complex of data analysis tasks.Simple data examples are integrated throughout so you can explorethe capabilities and versatility of R. Along the way, you'll alsolearn how to carry out a range of commonly used statisticalmethods, including Analysis of Variance and Linear Regression. Bythe end, you'll be able to effectively and efficiently analyze yourdata and present the results. Beginning R: Discusses how to implement some basic statistical methods suchas the t-test, correlation, and tests of association Explains how to turn your graphs from merely adequate to simplystunning Provides you with the ability to define complex analyticalsituations Demonstrates ways to make and rearrange your data for easieranalysis Covers how to carry out basic regression as well as complexmodel building and curvilinear regression Shows how to produce customized functions and simple scriptsthat can automate your workflow wrox.com Programmer Forums Join our Programmer to Programmer forums to ask and answerprogramming questions about this book, join discussions on thehottest topics in the industry, and connect with fellow programmersfrom around the world. Code Downloads Take advantage of free code samples from this book, as well ascode samples from hundreds of other books, all ready to use. Read More Find articles, ebooks, sample chapters and tables of contentsfor hundreds of books, and more reference resources on programmingtopics that matter to you. Wrox Beginning guides are crafted to make learning programminglanguages and technologies easier than you think, providing astructured, tutorial format that guides you through all thetechniques involved. Visit the Beginning R website at www.wrox.com/go/beginningr
A Course in Statistics with R by
Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject.
Understanding and Applying Basic Statistical Methods Using R by
Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R Understanding and Applying Basic Statistical Methods Using R uniquely bridges the gap between advances in the statistical literature and methods routinely used by non-statisticians. Providing a conceptual basis for understanding the relative merits and applications of these methods, the book features modern insights and advances relevant to basic techniques in terms of dealing with non-normality, outliers, heteroscedasticity (unequal variances), and curvature. Featuring a guide to R, the book uses R programming to explore introductory statistical concepts and standard methods for dealing with known problems associated with classic techniques. Thoroughly class-room tested, the book includes sections that focus on either R programming or computational details to help the reader become acquainted with basic concepts and principles essential in terms of understanding and applying the many methods currently available. Covering relevant material from a wide range of disciplines, Understanding and Applying Basic Statistical Methods Using R also includes: Numerous illustrations and exercises that use data to demonstrate the practical importance of multiple perspectives Discussions on common mistakes such as eliminating outliers and applying standard methods based on means using the remaining data Detailed coverage on R programming with descriptions on how to apply both classic and more modern methods using R A companion website with the data and solutions to all of the exercises Understanding and Applying Basic Statistical Methods Using R is an ideal textbook for an undergraduate and graduate-level statistics courses in the science and/or social science departments. The book can also serve as a reference for professional statisticians and other practitioners looking to better understand modern statistical methods as well as R programming. Rand R. Wilcox, PhD, is Professor in the Department of Psychology at the University of Southern California, Fellow of the Association for Psychological Science, and an associate editor for four statistics journals. He is also a member of the International Statistical Institute. The author of more than 320 articles published in a variety of statistical journals, he is also the author eleven other books on statistics.
Please contact Arun Deo adeo@unitec.ac.nz from the Research Office if you need further help.
You need both R and R-Studio to be installed into your computer in order to to run R programming language. The links for installation are: