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These are notes that were turned into a book: Using R for Introductory Statistics, published Fall 2004 by Chapman Hall/CRC Press. The book is a substantial improvement. These notes are left up as they are a bit cheaper. The simpleR package is now inside the UsingR package available from CRAN. In the Windows GUI, this may be installed from a menubar item. Otherwise, the following command

> install.packages("UsingR")

will work if you have sufficient permissions to install a package, or have set up R to install to a local area.

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Introduction

1 Introduction

1.1 What is `R`

These notes describe how to use R while learning introductory statistics. The purpose is to allow this fine software to be used in "lower-level" courses where often MINITAB, SPSS, Excel, etc. are used. It is expected that the reader has had at least a pre-calculus course. It is the hope, that students shown how to use R at this early level will better understand the statistical issues and will ultimately benefit from the more sophisticated program despite its steeper ``learning curve''.
The benefits of R for an introductory student are

R is free. R is open-source and runs on UNIX, Windows and Macintosh.
R has an excellent built-in help system.
R has excellent graphing capabilities.
Students can easily migrate to the commercially supported S-Plus program if commercial software is desired.
R's language has a powerful, easy to learn syntax with many built-in statistical functions.
The language is easy to extend with user-written functions.
R is a computer programming language. For programmers it will feel more familiar than others and for new computer users, the next leap to programming will not be so large.

What is R lacking compared to other software solutions?

It has a limited graphical interface (S-Plus has a good one). This means, it can be harder to learn at the outset.
There is no commercial support. (Although one can argue the international mailing list is even better)
The command language is a programming language so students must learn to appreciate syntax issues etc.

R is an open-source (GPL) statistical environment modeled after S and S-Plus (http://www.insightful.com). The S language was developed in the late 1980s at AT&T labs. The R project was started by Robert Gentleman and Ross Ihaka of the Statistics Department of the University of Auckland in 1995. It has quickly gained a widespread audience. It is currently maintained by the R core-development team, a hard-working, international team of volunteer developers. The R project web page

http://www.r-project.org

is the main site for information on R. At this site are directions for obtaining the software, accompanying packages and other sources of documentation.

1.2 A note on notation

A few typographical conventions are used in these notes. These include different fonts for urls, R commands, dataset names and different typesetting for