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Kaj_Sotala comments on A History of Bayes' Theorem - Less Wrong
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Fair point. Still, a person who hasn't read the book can't know whether lines such as "at age 62, Laplace — the world's first Bayesian — converted to frequentism" are from the book or if they were something you came up when summarizing.
In previous discussions on the topic, I've seen people express the opinion that the fierce debates are somewhat of a thing of the past. I.e. yes there have been fights, but these days people are mostly over that.
I took this as a successful attempt at humor.
This is something I was told over and over again by professors, when I was applying to grad school for biostatistics and told them I was interested in doing specifically Bayesian statistics. They mistook my epistemological interest in Bayes as like... ideological alignment, I guess. This is how I learned 1. that there were fierce debates in the recent past and 2. most people in biology don't like them or consider them productive.
I'm not sure that the debates were even THAT recent. I think your professsors are worried about a common failure mode that sometimes creeps up- people like to think they know the "one true way" to do statistics (or really any problem) and so they start turning every problem into a nail so that they can keep using their hammer, instead of using appropriate methodology to the problem at hand.
I see this a fair amount in data mining, where certain people ONLY use neural nets, and certain people ONLY use various GLMs and extensions and sometimes get overly-heated about it.
Thanks for the warning. I thought the only danger was ideological commitment. But--correct me if I'm wrong, or just overrecahing--it sounds like if I fail, it'll be because I develop an expertise and become motivated to defend the value of my own skill.
No, more like you'll spend months (or more) pushing against a research problem to make it approachable via something in a Bayesian toolbox when there was a straightforward frequentist approach sitting there all along.