To run **Rweb** just type the **R **(or Splus) code you want
to execute into the text window and
then click on the submit button.
You will get a new html page with the text output of your code followed
by the graphical output (if any) from your code.

Below the submit button is a text area where you can enter the
URL for a Web accessible dataset and a browse button for selecting a
dataset on your computer.
Either way, the dataset will be read in using
**read.table**
with **header=T**
and stored in a dataframe called **X**.
The dataframe, **X**, will then be attached so you can use the
variable names.
Eventually I hope to add several other options for data entry ... let me
know if you have any suggestions.

If you use the back button on your browser to come back to this page you can modify your old code and then resubmit it, or you can clear the text area and type in all new code. The computer time for all of this is donated by the Department of Mathematical Sciences, Montana State Univeristy.

A tutorial on S may help you if you are not familiar with R or S language. If you need a little help with R functions you can use the R function help page (this is just the help page included in the R distribution).

If you don't know how to program in R here is a short code snippet that shows you a little bit about what R can do. You should cut the following code and then paste it into the text window.x <- rnorm(100) # 100 random numbers from a normal(0,1) distribution y <- exp(x) + rnorm(100) # an exponential function with error result <- lsfit(x,y) # regress x on y and store the results ls.print(result) # print the regression results plot(x,y) # pretty obvious what this does abline(result) # add the regression line to the plot lines(lowess(x,y), col=2) # add a nonparametric regression line (a smoother) hist(result$residuals) # histogram of the residuals from the regression