alt Hacker NewsThank you. The main problem with Bayesian statistics is that if the outcome depends on your priors, your priors, not the data determine the outcome.
Bayesian supporters often like to say they are just using more information by coding them in priors, but if they had data to support their priors, they are frequentists.
If they were doing frequentist inference they wouldn’t be using priors at all and there is nothing frequentist in using previous data to construct prior distributions.