Bayesians is a textbook example of a sect.
This is just an abstract framework superimposed on some aspects of reality and has nothing to do with its processes.
Let me repeat: a superimposed set of abstractions. Nothing more.
This is just an abstract framework superimposed on some aspects of reality and has nothing to do with its processes.
Let me repeat: a superimposed set of abstractions. Nothing more.
There are communities which pick up Bayes Theorem in isolation (i.e. without any other statistical education or knowledge) and apply it to every debate and discussion under the Sun, often pontificating about how rational they're being about "updating their priors." But using Bayes theorem qualitatively instead of quantitatively - and without regard for its pitfalls - often leads to confirmation bias in which someone lends a veneer of rigorous probability to something they already unconsciously believed anyway. It's also sometimes used to dress up pseudoscience with intellectual polish, and it takes work to unpack those errors.
Bayesian probability is not a panacea, and does not displace frequentist probability. The two paradigms are fully compatible (you can move from one to the other via inversion of the estimator function). But they answer different questions, both of which are important. It is also easy to make statistical errors in both paradigms.
Recall, most statisticians are not Bayesian. Most science is not Bayesian and its not because everyone is naive or just too stupid to see. The Bayesian approach is well known and long standing but it takes using it in anger to see what it is good for and what it is not.