> I can't fathom how one can reasonably argue that frequentist approaches are always inferior, even in applied statistics. My original claim is broader than I

> I can't fathom how one can reasonably argue that frequentist approaches are always inferior, even in applied statistics. My original claim is broader than I wanted it to be. The fact is, a Frequentist approach will always be less accurate than the correct application of probability theory. But of course, > Bayesians know that using probability theory correctly is sometimes intractable (combinatorial explosion and all that). In those cases, they will use approximations. But at least, they will know it's an approximation. https://news.ycombinator.com/item?id=6793905 https://news.ycombinator.com/item?id=6793905 The key to the Bayesian outlook is to remember that no matter what, there is a correct answer, even if you can't afford to compute it. As Eliezer Yudkowsky put it, there are laws of thought. Want to use Frequentist tools? Sure, why not. Just remember that they often violate the laws of ideal though. Some inaccuracy inevitably ensues.