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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 ( 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
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

longer sequences of R commands.     
and for

    Data sets.
Copyright © John Verzani, 2001-2. All rights reserved.

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