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Statistics: an introduction using R Michael J. Crawley
Publisher: Wiley

However R in its very own nature is a nothing more than a language to perform statistical analysis. This is an introduction to tools for engaging the community to improve your R code and collaborate with others. Simulations in *Stata* and #R# - github.com/EconometricsBySimulation/ Bulk search for domain names using R . I teach into a first-year subject that all science majors take called “Introduction to Modelling Natural Systems” which uses Excel, though we agonized about whether to use that or something like Splus. One such language that complements subject of statistics is the R Language. R is a powerful open-source programming language for data analysis, statistics, and visualization, but much of its power derives from a large, engaged community of users. Original Code * Statistical programs often lack the built in capabilities to create tables for publication. *This example is cribbed from Michael Crawley's “Statistics: an introduction using R”. Among other things, they've developed a very handy-looking R package called mosaic, which simplifies the use of R for basic statistical and modeling task, and alters the output in a way designed to be friendly and people new to both statistics and to R. This a brief guide to using R in collaborative, social ways. It's up to you to check that the software has correctly attributed degrees of freedom; fail to do this and beware the wrath of peer reviewers. This tutorial is intended to introduce users quickly to the basics of R, focusing on a few common tasks that biologists need to perform some basic analysis: load a table, plot some graphs, and perform some basic statistics.