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Statistics 200: Lab 12-13 (Friday 17 & 24 April
Today's tasks: Now you get a chance to show what you have learned, by
using Splus to do something useful.
For the next two lab sessions you should work on a project involving
Splus. During the final lab session, on Friday, April 24th, you will get
to explain to the class what you have done. You need to get started quickly.
Some possible projects
Some of you already have data sets that you want to work with. Try to use
the graphics tools in Splus to show what you have, and what sort of analysis
might be possible.
Write a useful Splus function. For example, it would be nice to have a
modified version of read.table() that didn't suffer from the overhead of
writing large temporary files to extract headers. I think it can be done
using scan() more efficiently. I would like to have a function like:
that would return a data frame. For example, if a file foobar.txt contained
and so on, then I would like
junk <- my.read.table("foobar.txt",sep=":",datatypes="FCFN")
to return a data frame with factor variables junk$court and junk$disq,
a character variable junk$date, and a numeric variable junk$count. If you
want to get fancy you might allow more flexible forms for the datatypes.
For folks in the Linear Models course, we would accept a combined project
if it contained enough material. For example, you might be able to develop
some functions to bootstrap regression residuals and produce some interesting
graphical displays. Talk to Marten about this one.
Find an example where trellis graphics is really a big improvement over
the simpler Splus tools. Create some deviishly clever panel functions.
Anything else that you can think of.