4 ms·

There were some pretty savage fights between Bayesians and Frequentists over the 20th century (see e.g. The Theory That Would Not Die), but by now there is peac

There were some pretty savage fights between Bayesians and Frequentists over the 20th century (see e.g. The Theory That Would Not Die), but by now there is peace. The main thing that's changed is computers, algorithms, and software have gotten a lot faster. So you can actually do bayesian inference on nontrivial models and datasets. The math behind Bayesian methods is pretty solid and indisputable. The main controversy is how to specify priors. And you can always use uninformative priors if you have to.

eli_gottlieb 9y ago
>The math behind Bayesian methods is pretty solid and indisputable. The main controversy is how to specify priors. But as the Bayesians always point out, specifying which sampling procedures, test statistics, and inferences to run under frequentist statistics also amounts to inserting subjective judgements into your statistical analyses, soooo... you might as well just pick the one that reviewers in your field like, or that works for your problem.