Teaching Bayesian statistics? Looking for advice.

I'm afraid the job market for stats teachers is not great - most university/college departments I know of don't hire external instructors to teach stats. Instead they're often taught by lecturers/asst professors whose research specialties also involve some level of statistical sophistication (that is, "ability to teach stats" as a secondary selection criterion rather than primary). In the US system especially there also tends to be a relatively large pool of advanced PhD students who are much cheaper to employ than tenure track faculty, but who also have the requisite skills to teach stats. Teaching fellows and adjunt faculty (ie people hired just to teach) tend to be hired from within.

Teaching at community college level is a possibility, and strangely enough the pay tends to be much higher than at the university level (shockingly low, if you didn't already know). But this comes at the cost of a very high workload, and specifically related to your area of interest, you are likely to come across students who lack even the most basic numeracy skills - multiplication and division.

But then it comes to the big question - can one actually teach Bayesian statistics at the undergraduate level? This depends on the field. In psychology, for example, I think the answer at the moment is a definitive "no". A telling example is John Kruschke at Indiana - one of the main proponents of Bayesian statistics. Here you can see his open letter to the field calling for an end to frequentist approaches. Yet in his introductory undergraduate stats course he explicitly avoids Bayesian statisics (see his course notes here ) and even at the graduate level he sticks mainly to frequentist approaches, albeit with a healthy dose "take the next course which explains how to do things right). Although it's clear that the transition is coming in this field (for example the message being delivered by EJ Wagenmakers and many others) it has not yet trickled down to undergraduates - who need to know frequentist statistics, if for no other reason than to understand this otherwise mystical jargon that appears in all the research articles they are likely to read in their undergraduate careers.

Sorry, I've started to feel like I'm rambling ... research methods instruction is one of those things I am passionate about, and your post compelled me to register and post for the first time after years of lurking.

I did send in an application to the Center for Modern Rationality but I haven't heard back

Please email me (elcenia@gmail.com) and tell me which types of work you wanted. There has been a spreadsheet-tracking issue, and I'm not sure who I have and haven't reached yet. (I'm considering just mass-mailing everybody on the list with "if you haven't heard from me before, please let me know and I can give you sample work". Thoughts on whether this would be more obnoxious than helpful?)

All of the really smart professors I know personally who have an opinion on the topic are Bayesians, Less Wrong as a community prefers Bayesianism, and I prefer it.

Is this how you would respond to a hypothetical student of yours asking why you're not a frequentist? Sorry for the snark, but you are considering a career choice where you would be a voice for Bayesianism to your students and fellow faculty. I think you owe it to those who want Bayesian methods to be treated seriously to acquaint yourself with de Finetti's theorem, Cox's theorem, the frequentist consistency (or lack thereof) of Bayesian procedures, etc.

Also, I'm pretty sure this is not the best way you could get paid to raise the sanity or rationality waterline, given your background. Think about the marginal effect of taking such a job. Best case, you'll either teach a Bayesian stats courses that otherwise wouldn't be taught due to lack of faculty or replace someone who would otherwise teach it (that person will probably be have better or equal academic credentials and might be less enthusiastic about Bayesianism). But students who would choose to take a Bayesian stats course will probably do fine anyways. Teaching intro (frequentist) stats well or doing private tutoring for students stuck in bad intro stats courses will be more likely to make a difference.

Bayesian statistics was a third year course at the universities I've attended. Keep in mind that Bayesian statistics uses the probability theory that is given in most probability and statistics modules, and requires distributional knowledge, something also taught by frequentist statistics. First year students will not have the knowledge of probability distributions or algebra to be able to find posteriors. And, of course, if you want to apply Bayesian statistics in practice you need some kind of programming skill, as most programs that do Bayesian analysis are not user friendly (a plague on winbugs house..).

Heres what Bayesian statistics courses tend to teach (in my experience) -the basis of bayesian statistics (usually in light amounts) -priors, and obtaining posteriors from them. Usually applied to simple examples with conjugate priors, a tough exam question might be to obtain the posterior of the mean mu and variance sigma of a normal distribution with normal prior and inverse gamma prior. -Jeffrey's prior (so they need to know what an information matrix is) -an introduction to MCMC techniques, particularly gibbs sampling and random walk metropolis hastings.

I'd suggest going into research first, to improve your credentials and also to gain a solid understanding of statistics. If you don't like biology, business schools use a lot of Bayesian techniques.

I haven't read Bolstad, but I think that grokking the first 3-ish chapters of Jaynes seems like a reasonable requirement for being able to explain why probability looks the way it does. The actual "methods" chapters after that aren't really useful/necessart for undergrads, except for the simple stuff like "given some data, what's the likelihood ratio for your hypothesis? How about the null hypothesis?" You could always jump into teaching without re-reading that, but iunno.

I don't know about helping you find a job, but as a biology grad student, I wish there were someone teaching a Bayesian course at my university.

What about creating a web application or web-based tutorial that teaches Bayesian statistics? Something like

http://eloquentjavascript.net/contents.html (check out the interactive examples)

or the recent Stanford online classes. (Probably not something you could easily get paid to do though...)