> All statisticians use prior information in their statistical analysis. Non-Bayesians express their prior information not through a probability distribution on parameters but rather through their choice of methods.
Also, from the comments:
>My problem is ultimately not with the cartoon. My problem is that there are practitioners and teachers of statistics who spread cartoonish ideas about statistical methods without recognizing these ideas are inaccurate.
I'm not sure how it can be a good idea to be choosing from various statistical methods based on which one will give you the sort of answer you intuitively think is correct. I mean, if you're going to bite the bullet and bring priors into your analysis in an ad-hoc way like that, why not just acknowledge their existence mathematically?
When you are reporting, say, a p-value from your ANOVA F-test, you are making formal mathematical assumptions, such as normal marginal distribution of your dependent variable. A lot of Frequentist methods (hypothesis testing) are really just mathematical shortcuts from times when computation was more expensive. The problem is, many people tend to misuse the tests where they are not appropriate either because those give "better" answers, or simply out of ignorance.
Right, but the way you deal with the situation in the comic is going to end up being much fuzzier and more subjective issue of picking you reference classes.
> All statisticians use prior information in their statistical analysis. Non-Bayesians express their prior information not through a probability distribution on parameters but rather through their choice of methods.
Also, from the comments:
>My problem is ultimately not with the cartoon. My problem is that there are practitioners and teachers of statistics who spread cartoonish ideas about statistical methods without recognizing these ideas are inaccurate.