My friend and I want to do a hands on tutorial on Bayes theorem for the Seattle LessWrong group. Neither of us have done this before, so we're searching for prior art; techniques that other people have tried before and descriptions of how they turned out.
What are good techniques and resources for teaching bayes theorem? Reports of both successes and failures are useful, I'd like to know what not to do in addition to what to do.
The audience is a group of ~8 programmers and natural science students. They'll be smart and capable but not necessarily used to doing much math.
Best Answer
I have to recommend the book "Doing Bayesian Data Analysis" by John Kruschke (Indiana). Having sampled a few "introductory" texts over the last while, this one really shines.
There are many really well explained points but I suppose the best lever he uses to introduce the notion of combining prior and evidence is to introduce Bayes in the context of a multi-way table, where the data cause you to restrict your attention to one row, and sum over marginals to get a posterior for the cell. It is then easily expansible to continuous variables and thence to multi-way distributions.
Might be worth your while looking at it.