Doctors, at least 15 years ago, were definitely bad at statistics.
They were not required to take a statistics course at all. Most programs would require Algebra and Calculus as part of their science reqs.
Some would maybe take one basic research course, and they would then become obsessed with p values of 0.05.
They did not have a basic understanding of how to interpret research unless they were an auto didactic and went out of their way to improve. It's something my director (a doctor and software engineer), and the Dean complained about relentlessly.
You reminded me about another idiosyncrasy: Doctors are addicted to double blind randomized control trials.
Which yes, those are powerful. But good evidence can come from many other study designs. Especially when mechanisms and first principles are being studied.
Isn't one of the bigger problems with ChatGPT that it's much too supportive of whatever the human is talking about?
But it does require to know the bias that LLMs have ahead of testing this.