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Bayesian Statistics: The three cultures

(statmodeling.stat.columbia.edu)
309 points luu | 2 comments | 26 Jul 24 17:15 UTC | HN request time: 0.001s | source
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thegginthesky ◴[26 Jul 24 17:55 UTC] No.41080693[source]▶
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

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RandomThoughts3 ◴[26 Jul 24 18:28 UTC] No.41080979[source]▶
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.

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1. parpfish ◴[26 Jul 24 18:36 UTC] No.41081068[source]▶
I don’t think mathematical ability has much to do with it.

I think it’s useful to break down the anti-Bayesians into statisticians and non-statistician scientists.

The former are mathematically savvy enough to understand bayes but object on philosophical grounds; the later don’t care about the philosophy so much as they feel like an attack on frequentism is an attack on their previous research and they take it personally

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2. mturmon ◴[26 Jul 24 18:55 UTC] No.41081239[source]▶
This is a reasonable heuristic. I studied in a program that (for both philosophical and practical reasons) questioned whether the Bayesian formalism should be applied as widely as it is. (Which for many people is, basically everywhere.)

There are some cases, that do arise in practice, where you can’t impose a prior, and/or where the “Dutch book” arguments to justify Bayesian decisions don’t apply.