I do need to read up on those; Jaynes talks about the implications of Cox’s theorem but doesn’t go into it directly, so I’m only vaguely familiar. Thank you for the reading suggestions. I did plan to talk about those issues in the introduction of the course. Bolstad has an intro section justifying the Bayesian perspective, as well.
I think I picked that particular set of justifications because educators in general don’t care about mathematical proofs, they care about what will be useful for the students to know how to do; in biology, the point of knowing statistics is to be able to read and write scientific papers, and the vast majority of papers are written using frequentist statistics. Proofs will not convince them; the fact that top professors are using Bayesian methods might.
My expectation was that I would replace a mediocre frequentist statistics lecturer with an excellent bayesian statistics lecturer within the same class. The class that I TA is taught by multiple professors, and at least one of them teaches from a Bayesian perspective. Professors have ridiculous academic freedom; one professor covers only basic t-tests, while another professor covers everything from linear regressions to the KS test to chi-squared to two-way ANOVA, and it’s still the same course listing. So long as the students aren’t complaining about failing, the university does not care. The students can try to sign up for a different professor, and will do so if they hear another prof is easier, but they still have to take the class, so even harder professors still have full sections (especially if their version has a reputation for being very useful/educational).
So, assuming that I would be hired to teach statistics and could choose to teach either frequentist or Bayesian, I see very little point in teaching frequentist. I could also reach vastly more students lecturing than I could via tutoring, probably 80ish vs 10ish.
I think the students that are interested in learning Bayesian stats should have the option available; I think there are probably a fair number of students who are smart, savvy, and motivated enough to sign up for a stronger stats course but aren’t quite good enough to teach it to themselves.
I think I would almost rather not teach statistics than teach straight frequentist. I am really sick of teaching kids stuff that I know is suboptimal. I mean, I could do a good job of it, but raising the waterline isn’t worth being miserable.
I do need to read up on those; Jaynes talks about the implications of Cox’s theorem but doesn’t go into it directly, so I’m only vaguely familiar. Thank you for the reading suggestions. I did plan to talk about those issues in the introduction of the course. Bolstad has an intro section justifying the Bayesian perspective, as well.
I think I picked that particular set of justifications because educators in general don’t care about mathematical proofs, they care about what will be useful for the students to know how to do; in biology, the point of knowing statistics is to be able to read and write scientific papers, and the vast majority of papers are written using frequentist statistics. Proofs will not convince them; the fact that top professors are using Bayesian methods might.
My expectation was that I would replace a mediocre frequentist statistics lecturer with an excellent bayesian statistics lecturer within the same class. The class that I TA is taught by multiple professors, and at least one of them teaches from a Bayesian perspective. Professors have ridiculous academic freedom; one professor covers only basic t-tests, while another professor covers everything from linear regressions to the KS test to chi-squared to two-way ANOVA, and it’s still the same course listing. So long as the students aren’t complaining about failing, the university does not care. The students can try to sign up for a different professor, and will do so if they hear another prof is easier, but they still have to take the class, so even harder professors still have full sections (especially if their version has a reputation for being very useful/educational).
So, assuming that I would be hired to teach statistics and could choose to teach either frequentist or Bayesian, I see very little point in teaching frequentist. I could also reach vastly more students lecturing than I could via tutoring, probably 80ish vs 10ish.
I think the students that are interested in learning Bayesian stats should have the option available; I think there are probably a fair number of students who are smart, savvy, and motivated enough to sign up for a stronger stats course but aren’t quite good enough to teach it to themselves.
I think I would almost rather not teach statistics than teach straight frequentist. I am really sick of teaching kids stuff that I know is suboptimal. I mean, I could do a good job of it, but raising the waterline isn’t worth being miserable.