This is a local Rweb server for the School of Statistics at the University of Minnesota.

Also available is the HTML documentation for the version of R on this server.

Rweb is a Web based interface to R (a statistical analysis package) that takes the submitted code, runs R on the code (in batch mode), and returns the output (printed and graphical). If you have any comments, criticisms, bug reports, or if you're just lonely you can email me (Jeff Banfield) at jeff@math.montana.edu. If you are interested in setting up your own Rweb server visit the Rweb Resources Page to download the source code and find links to supporting software.

R is a free statistical analysis package developed by Robert Gentleman and Ross Ihaka. It is almost source code compatible with S or Splus so if you have experience with those languages you should have no problem using Rweb. For information about R you can read the R introduction page, contact the R authors , or visit the R Archive.

If you would like to learn more about using R you can start with the book An Introduction to R written by the R team. It is available on the web, since it comes with the R documentation. The local version is here. It is also available as a PDF file that can be printed out at any CRAN mirror site. To download this book from the North American mirror click here.

Which Version Do You Want?

Rweb

A simple web interface to R that works on most browsers and requires knowledge of R (or Splus). You type in the code, click the submit button and a page with the results (analysis and graphs) is returned. This version of Rweb only requires a browser that can handle forms and graphics (if you do any plotting). There is a small code snippet at the end of the page in case you don't know R but you still want to try it out.

JavaScript Version of Rweb

This is the same Rweb as above but with a few display enhancements based on JavaScript. If your browser understands JavaScript this version of Rweb should work for you.

Rweb modules

These modules are designed as a point and click forms based interface to R for use in introductory statistics courses. Students do not need to know anything about writing programs in R. They choose a data set, the type of analysis, and the options for the analysis. The currently implemented analyses include Regression, Summary statistics and graphs, ANOVA, Two Way Tables, and a Probability calculator. The output includes printouts and graphs which can be cut and pasted into project writeups or printed out. I'm making the modules up as I go (both content and design) and I would love to have some advice. So, anybody that has an idea about improving these modules, please let me know.

© 1998 Jeff Banfield

Last Modified: 22-Feb-1999

Material Added: 26-Mar-2002 by Charles Geyer (charlie@stat.umn.edu)