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wedrifid comments on Case study: abuse of frequentist statistics - Less Wrong
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The central difficulty of Bayesian statistics is the problem of choosing a prior: where did it come from, how is it justified? How can Bayesians ever make objective scientific statements, if all of their methods require an apparently arbitrary choice for a prior?
Frequentist statistics is the attempt to do probabilistic inference without using a prior. So, for example, the U-test Cyan linked to above makes a statement about whether two data sets could be drawn from the same distribution, without having to assume anything about what the distribution actually is.
That's my understanding, anyway - I would also be happy to see a "Frequentism for Bayesians" post.
Without acknowledging a prior.
Some frequentist techniques are strictly incoherent from a Bayesian point of view. In that case there is no prior.
I believe you and would like to know some examples for future reference.
The OP is one such -- Bayesians aren't permitted to ignore any part of the data except those which leave the likelihood unchanged. One classic example is that in some problems, a confidence interval procedure can return the whole real line. A mildly less pathological example also concerning a wacky confidence interval is here.
Yes; in Bayesian terms, many frequentist testing methods tend to implicitly assume a prior of 50% for the null hypothesis.