What are good techniques and resources for teaching bayes theorem hands on?
Guy Srinivasan 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.
We expect ~8 programmers and natural science students to show up.
Make the presentation in terms of likelihood ratios rather than probabilities. Then Bayes becomes plain multiplication. Multiple hypotheses and multiple pieces of evidence are also easier to handle in this format.
Since thinking of Bayes like this, I’m more likely to do simple calculations in my head and I have a better handle on the proper size of an update. Previously, it didn’t click that going from 0.5 to 0.75 takes the same amount of evidence as 0.75 to 0.9 and 0.9 to 0.96. In likelihood terms, that is going from 1:1 to 3:1 to 9:1 to 27:1, with an additional 3:1 piece of evidence at each stage. Eliezer is rewriting An Intuitive Explanation with likelihood ratios as well.
This is my favorite explanation. It’s short and to the point, and the visuals are excellent.
I like the Intuitive Explanation of Intuitive Explanation of Bayes’ Theorem a lot, but it might be too simple for programmers and natural science students.
Have you looked at Eliezer’s intuitive explanation? I think a verbalized version of that might be effective.