Bayesian Statistics: The three cultures

I miss the college days where professors would argue endlessly on Bayesian vs Frequentist.

The article is very well succinct and even explains why even my Bayesian professors had different approaches to research and analysis. I never knew about the third camp, Pragmatic Bayes, but definitely is in line with a professor's research that was very through on probability fit and the many iteration to get the prior and joint PDF just right.

Andrew Gelman has a very cool talk "Andrew Gelman - Bayes, statistics, and reproducibility (Rutgers, Foundations of Probability)", which I highly recommend for many Data Scientists

I’m always puzzled by this because while I come from a country where the frequentist approach generally dominates, the fight with Bayesian basically doesn’t exist. That’s just a bunch of mathematical theories and tools. Just use what’s useful.

I’m still convinced that Americans tend to dislike the frequentist view because it requires a stronger background in mathematics.

I think the distaste Americans have to frequentists has much more to do with history of science. The Eugenics movement had a massive influence on science in America a and they used frequentist methods to justify (or rather validate) their scientific racism. Authors like Gould brought this up in the 1980s, particularly in relation to factor analysis and intelligence testing, and was kind of proven right when Hernstein and Murray published The Bell Curve in 1994.

The p-hacking exposures of the 1990s only fermented the notion that it is very easy to get away with junk science using frequentest methods to unjustly validate your claims.

That said, frequentists are still the default statistics in social sciences, which ironically is where the damage was the worst.

What is the protection against someone using a Bayesian analysis but abusing it with hidden bias?