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I don't understand why Bayesian statistics needs to be an "-ism", and still less why other statistics needs to be an "-ism" too. I don't understand why people f

by afafsd 12y ago

I don't understand why Bayesian statistics needs to be an "-ism", and still less why other statistics needs to be an "-ism" too. I don't understand why people feel the need to line up on one side or the other or get so worked up about it. Other branches of mathematics seem to avoid this kind of thing, they have no problem with the idea that there's different ways of doing the same thing. It actually discourages me from learning more about Bayesian statistics, because the whole thing sometimes comes off as a cult.

lutusp 12y ago
> I don't understand why Bayesian statistics needs to be an "-ism", and still less why other statistics needs to be an "-ism" too. I don't understand why people feel the need to line up on one side or the other or get so worked up about it. Don't get hung up on the terminology, instead pay attention to the ideas behind the terms. The Frequentist and Bayesian approaches are very different, and produce different outcomes, so they deserve to be understood and their differences sorted out. For example, and without providing all the technical details, using a Frequentist analysis a decision was made to recommend breast cancer screening x-rays for women over a given age. Later, after serious problems arose, a Bayesian approach showed that the false positive rate was 5 to 1 (5 false positives to 1 real cancer detection), which meant many more people were given the false news that they had cancer than those who actually did. https://www.princeton.edu/~achaney/tmve/wiki100k/docs/Bayes__theorem.html https://www.princeton.edu/~achaney/tmve/wiki100k/docs/Bayes_... This is not to exalt the Bayesian approach over the Frequentist, because both have their place, it is only to show how dramatic the difference can be.
- pessimizer 12y ago
  It seems like you're confusing Bayes' Theorem with Bayesian statistics. Bayes probably wasn't a Bayesian, and everybody uses Bayes' theorem.
  - lutusp 12y ago
    > It seems like you're confusing Bayes' Theorem with Bayesian statistics. Yes, a tempest in a teapot. Anyone caught using Bayes' name without qualifying the use is placed in the same position as someone referring to the Victorian Era without mentioning that Victoria wasn't a Victorian. In most cases, it's not worth the digression.

by afafsd 12y ago

lutusp 12y ago

> I don't understand why Bayesian statistics needs to be an "-ism", and still less why other statistics needs to be an "-ism" too. I don't understand why people feel the need to line up on one side or the other or get so worked up about it. Don't get hung up on the terminology, instead pay attention to the ideas behind the terms. The Frequentist and Bayesian approaches are very different, and produce different outcomes, so they deserve to be understood and their differences sorted out. For example, and without providing all the technical details, using a Frequentist analysis a decision was made to recommend breast cancer screening x-rays for women over a given age. Later, after serious problems arose, a Bayesian approach showed that the false positive rate was 5 to 1 (5 false positives to 1 real cancer detection), which meant many more people were given the false news that they had cancer than those who actually did. https://www.princeton.edu/~achaney/tmve/wiki100k/docs/Bayes__theorem.html https://www.princeton.edu/~achaney/tmve/wiki100k/docs/Bayes_... This is not to exalt the Bayesian approach over the Frequentist, because both have their place, it is only to show how dramatic the difference can be.

pessimizer 12y ago
It seems like you're confusing Bayes' Theorem with Bayesian statistics. Bayes probably wasn't a Bayesian, and everybody uses Bayes' theorem.
- lutusp 12y ago
  > It seems like you're confusing Bayes' Theorem with Bayesian statistics. Yes, a tempest in a teapot. Anyone caught using Bayes' name without qualifying the use is placed in the same position as someone referring to the Victorian Era without mentioning that Victoria wasn't a Victorian. In most cases, it's not worth the digression.