What were they reluctant to learn? Why do they need to learn it?

Plenty of engineers have to take an introductory stats course, but it's not clear why you'd want your engineers to learn bayesian statistics? I would be surprised if they could correctly interpret a p-value or regression coefficient, let alone one with interaction effects. (It'd be wholly useless if they could, fwiw).

It'd be nice if the statisticians/'data scientists' on my team learned their way around the CI/CD pipelines, understood kubernetes pods, and could write their own distributed training versions of their pytorch models, but division-of-labor is a thing for a reason, and I don't expect them to nor need them to.