

This xkcd comic (Frequentists vs. Bayesians) makes fun of a frequentist statistician who derives an obviously wrong result.

However it seems to me that his reasoning is actually correct in the sense that it follows  the standard frequentist methodology. 

So my question is "does he correctly apply the frequentist methodology?" 


If no: what would be a correct frequentist inference in this scenario? How to integrate "prior knowledge" about the sun stability in the frequentist methodology?
If yes: wtf? ;-)


The main issue is that the first experiment (Sun gone nova) is not repeatable, which makes it highly unsuitable for frequentist methodology that interprets probability as estimate of how frequent an event is giving that we can repeat the experiment many times. In contrast, bayesian probability is interpreted as our degree of belief giving all available prior knowledge, making it suitable for common sense reasoning about one-time events. The dice throw experiment is repeatable, but I find it very unlikely that any frequentist would intentionally ignore the influence of the first experiment and be so confident in significance of the obtained results.

Although it seems that author mocks frequentist reliance on repeatable experiments and their distrust of priors, giving the unsuitability of the experimental setup to the frequentist methodology I would say that real theme of this comic is not frequentist methodology but blind following of unsuitable methodology in general. Whether it's funny or not is up to you (for me it is) but I think it more misleads than clarifies the differences between the two approaches.
