> Frequentist and Bayesian statistics are different tools that answer different questions. Arguing whether one is better than the other is like arguing whether

> Frequentist and Bayesian statistics are different tools that answer different questions. Arguing whether one is better than the other is like arguing whether one should drink water or eat bread. Astronomy and astrology also answer different questions, it's just that astrology doesn't answer the questions we're interested in, and it doesn't even do a great job with the questions it does purport to answer. When quantifying uncertainty, the only quantity of interest is the posterior probability, which Bayesian methods provide and frequentist methods don't. Period. The only reason we accept a likelihood instead is because it can provide a reasonable approximation and might be faster or easier to calculate, and the only reason we'd accept a p-value over the full likelihood function is when we need a quick-and-dirty metric of the importance of a variable or an intervention. These are all valid reasons, and heck, few things are more useful than a quick (frequentist) OLS regression, but to then conclude that frequentist and Bayesian methods are entirely equal and complementary is disingenuous. A good blogpost which deconstructs this line of reasoning in more detail: http://www.bayesianphilosophy.com/how-science-can-permanently-fail/ http://www.bayesianphilosophy.com/how-science-can-permanentl...