resources

good stuff

The course text, Collaborative Statistics by Illowsky and Dean.
Some online stats tools (not R).
Two blogs that talk about the presentation of data in interesting (and often contradictory ways): junkcharts and information is beautiful.
A good site with examples of good and bad graphs. The ACCENT principles in particular give a good set of questions to ask of any graph you encounter (or create).
Some notes on probability and Pig that I wrote for a course a couple of years ago.

R

The R Project Homepage from which you can download R and access the Introduction to R (pdf) in an online format.
The in-built help system is good. To access the page about using "pie" for example, simply type "?pie" and hit return.
A sequence of online R tutorials by K. Black.
The R Cookbook, a nice guide that takes an approach that I think is very much in keeping with the class, is (or will be soon) on the reserve shelf in the library.
As we saw in class, googling specific topics can be very successful. Sites I've never gone to as a first step but are regularly very helpful and among my first choices to check out, other things being equal, when they show up in response to a query:
- the overflow network, especially...
- Stats Stackexchange (including answers to the question about good resources for learning R---check some out and report back!),
- Quick-R,
- more as I remember or discover them.
I haven't played with it much yet, but RSeek is a search engine designed to look for R-related material.
The graphs with the light grey background in the heating oil handout were generated with the add-on package ggplot2. As far as possible I'm trying not to get into the extra (but very minor) hassle of using packages outside the main R release, but this one is very tempting. The book is comprehensive and readable. The library has a copy, but you may as well assume that I have it---I seem to carry it back and forth at the moment so that it's always to hand. Chapter 2 (all you need to generate the graphs in the heating oil handout, I think) is freely available.
R-bloggers aggregates many blog posts with R content. Probably not a good source of solutions to problems you're having, but great for seeing what people are doing with R and for unexpected inspiration.
The file of R commands for dealing with distributions is attached as DistInR below.

data and examples

The cookie data.
The R code we used in class for the examples of Chapter 2: college board, soccer player height and student height.
The R code that generates the heating oil graphs (pdf), which will need you to save the three data files and change the code so that you read them in from the right place. (I haven't made any particular effort to explain the steps that led to the code, just what the final result was that I wanted.)
The math data for Assignment 2 is attached below as an Excel file: mathdata.xls. What I did with data for the First Two Years Committee is here.
The dice data and R commands are attached below as dicedata.csv and DiceStats.txt respectively.
The R session from class on 19th April is linked belows as Rfrom19apr.txt (quick intro to using t.test, chisq.test, etc.) and the one from 24th April (linear models; sharks and ice-cream) is there as Rfrom24apr.txt.