Took me a while to read (in this age of LLM, I'm proud of myself), but the key points are explained fairly well: the abuse of p-value and the advantages of Baye

Took me a while to read (in this age of LLM, I'm proud of myself), but the key points are explained fairly well: the abuse of p-value and the advantages of Bayesian statistics. So why has the latter not caught on? In my opinion, the fact that you need to specify a prior is not as much an advantage in practice. Sounds good in theory, but in practice, there are many phenomena and variables that we simply does not know that well to specify a distribution to it. Maybe if Bayesian statistics gets more popular and encourages raw data sharing, then the situation will be better, but for now, it is difficult still. All that said, despite being a practical challenge, being explicit about your assumptions is still an important benefit of the Bayesian approach, and I hope it gets adopted more and more.