The medical test paradox: Can redesigning Bayes rule help?

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Издатель Dec 27, 2020

About Likelihood Ratios, also sometimes called Bayes Factors*.
Viewer-supported: https://3b1b.co/bayes-factor-thanks
Home page: https://www.3blue1brown.com

The book by my friend Matt Cook about paradoxes mentioned at the end:
https://amzn.to/3aBrEzg

On the topic, I can't help also mentioning another paradox book I'm rather fond of by Bunch:
https://amzn.to/3mBDSKE

Another video on Bayes' theorem:
https://youtu.be/HZGCoVF3YvM

*As mentioned in the on-screen note at the end, while the terms "Bayes Factor" and "Likelihood Ratio" refer to the same ratio in this setting, where Bayes rule is used on the probability of an event with only two possible outcomes (you either have the disease or you don't), they do take on divergent meanings in more general contexts. Namely, if you have a continuous parameter you are trying to estimate, the two terms reflect two alternate approaches you can use in comparing hypotheses. In fact, some people take the phrase "Bayes factor" to _specifically_ refer to its use in this more continuous context.

If you want more details, Wikipedia actually has a really nice example discussing the difference:
https://en.wikipedia.org/wiki/Bayes_factor#Example

This post has some nice discussion of the distinction:
https://stats.stackexchange.com/questions/27345/likelihood-ratio-vs-bayes-factor

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