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Talk:Bayes' theorem

Nowadays, Talk:Bayes' theorem is a topic that is becoming more and more relevant in our society. Over the years, we have seen how Talk:Bayes' theorem has impacted our lives in various ways, from the way we communicate, to the way we carry out our daily activities. There is no doubt that Talk:Bayes' theorem has generated a great impact both individually and collectively, and that is why more and more people are seeking information and knowledge on this topic. In this article, we will thoroughly explore Talk:Bayes' theorem and analyze its influence on different aspects of our life.

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Interpretations Image

The assassin version of the image is literally an inferior visualization, and less intuitive. Specifically, it is less visually apparent that a character is “sus” or “an assassin” compared to having a beard, or wearing glasses. Quite frustrating that people are happy to argue for something that harms the transmissible of knowledge because it’s funny. Uwuo (talk) 04:10, 22 June 2023 (UTC)

@Uwuo: Though mental characteristics are harder to illustrate than physical ones, suspicion/guilt is a far better application of Bayes' theorem than beard/glasses, which has no causal relationship. Cheers, cmɢʟee⎆τaʟκ 00:15, 2 July 2023 (UTC)
@Cmglee: Why do we need any visible attributes at all? Can't we just stick to plain numbers? What additional information do six face icons contain that a plain digit 6 doesn't? All the examples in the #Examples section work perfectly with digits, why can't #Interpretations do the same? --CiaPan (talk) 18:40, 2 July 2023 (UTC)
I support the use of a visual representation. I support the present visual over the beards and glasses visual because beards and glasses have no connection whereas being suspicious and being an assassin are believably connected. However, I also support improving the current diagram and even replacing it with something else, so long as the two variables have some connection. In the current diagram, being an assassin is indicated by a dagger. That one makes sense. Being suspicious is indicated by what? Is it a bushy eyebrow? Maybe an eyepatch would be better. Constant314 (talk) 18:49, 2 July 2023 (UTC)
Thanks, @Constant314. https://onlinelibrary.wiley.com/doi/abs/10.1111/jopy.12396 concludes that "distinctive eyebrows reveal narcissists' personality to others, providing a basic understanding of the mechanism through which people can identify narcissistic personality traits with potential application to daily life."
I've considered changing it to having some bloodstains (also starts with "B") I'll change it if you concur. Cheers, cmɢʟee⎆τaʟκ 19:15, 2 July 2023 (UTC)
I like that. See a man with blood stains on him and it is more likely he is an assassin. Constant314 (talk) 21:30, 2 July 2023 (UTC)
What have i stumbled upon LuckTheWolf (talk) 08:57, 9 October 2023 (UTC)
It does seem needlessly distracting (if the reader gets the Among Us reference) or confusing (if they don't) to have the assassins also wearing little visors and backpacks.
Maybe the suspicion marker could be a cloak, to go with the dagger? Belbury (talk) 17:13, 24 April 2024 (UTC)
While it may make no difference to you, some people are more visually minded and find it easier to understand or learn concepts when given concrete representations. Cheers, cmɢʟee⎆τaʟκ 19:10, 2 July 2023 (UTC)
@Uwuo this is why we can't have nice things Mihnea Liliac (talk) 17:04, 22 October 2025 (UTC)

Spelling of Bayes's Theorem

While I understand the standard in practice for this (and numerous other mathematical) theorem(s) is to use only the apostrophe after the last 's' of the name (& omit the final possessive 's'), this does not make any grammatical sense.

The final s (after the apostrophe) is omitted in plural possessives, and only when they end in s due to the pluralisation. Bayes fits neither of these rubric, as (for starters), Thomas Bayes was a singular person.

Unless there is a rationale for using this spelling (apart from lazy convention), I would suggest fixing this oversight. Jp.nesseth (talk) 23:42, 30 January 2024 (UTC)

This is not an oversight. It's been discussed, if not ad nauseam, at least ad tedium. You can bring it up again if you insist, but please look through the archives first. --Trovatore (talk) 23:49, 30 January 2024 (UTC)

Odds form of Bayes' theorem: Bayes rule

I think that Bayesian reasoning is much easier to understand through Bayes' rule: posterior odds = prior odds times likelihood ratio, where likelihood ratio = ratio of probabilities of the evidence, under each of the two hypotheses of interest. Example. We start off being 10 times more certain of hypothesis H than of hypothesis K. But we then observe evidence which is 1000 times more certain under K than under H. We end up being 100 times more certain of K than of H. Very powerful evidence has convinced us that something is much more likely true than not, even though initially it was rather unlikely. Richard Gill (talk) 10:06, 19 April 2025 (UTC)

I just saw that the article does have such a section. Hidden far away near the end of the very long article, after all the examples. I think it should be introduced near the beginning. Reason: it is intuitive. It does not depend on a complicated formula. Richard Gill (talk) 10:11, 19 April 2025 (UTC)

I think Bayes theorem should look like this, posterior odds equals prior odds times likelihood ratio.

Here A' and A are any two hypotheses; B is evidence. Richard Gill (talk) 13:27, 20 April 2025 (UTC)

Vs. likelihood

Equation was followed by text ~ "can be interpreted as likelihood because P(B|A)=P(A|B)", which is certainly not true. It's unclear to me what the simplest fix is -- perhaps introducing a notation for likelihood, and then rewriting it to use that notation instead of this wrong P notation? Jmacwiki (talk) 22:36, 15 August 2025 (UTC)

Maybe whoever wrote that intended to say "P(B|A) = L(A|B)" or something like that, and it got typo'd. Stepwise Continuous Dysfunction (talk) 21:15, 18 August 2025 (UTC)

Marginal probability vs. evidence

This may have been asked before. The article says, P(B) is called marginal probability. But in the top right hand overview box, the very first line reads Posterior = Likelihood × Prior ÷ Evidence. So here, P(B) is called evidence. I am aware that the word evidence is used differently in the article. Nevertheless there is an inconsistency.

D. S. Sivia in his book Data Analysîs writes on page 6 (his notation is (p(data|I) instead of p(B)): In some situations, like model selection, this term plays a crucial role. For that reason, it is sometimes given the special name of evidence. This crisp single word captures the significance of the entity, as opposed to older names, such as prior predictive and marginal likelyhood ... Such a central quantity ought to have a simple name, and evidence has been assigned no other technical meaning (apart from as a colloquial synonym for data).

The last parenthesis is just the problem :-) Still, I find Sivia's argument for the name evidence very good. Herbmuell (talk) 10:18, 11 November 2025 (UTC)

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