>Frequentists take the view that you should fix the parameters and integrate over the data. That is kind of weird to me. Integrating over the data makes a lot

>Frequentists take the view that you should fix the parameters and integrate over the data. That is kind of weird to me. Integrating over the data makes a lot of sense during methods development. If you're the inventor of some algorithm and you want to convince people that they should apply it to their data set, then you'd want to show that it works well on a range of possible data sets. It also makes some sense during policy development. Over your lifetime, you're going to see a lot of data sets, and having some policy about which statements about those data sets to believe can be useful. This policy doesn't have to be P<0.05. It could be six-sigma (like in physics) or something based on the false discovery rate (like in genomics). I don't think frequentism is always the right approach, but I do see a place for it.