Talk:Prior probability

message: The statement: "For example, Edwin T. Jaynes has published an argument [a reference here would be useful] based on Lie groups that if one is so uncertain about the value of the aforementioned proportion p that one knows only that at least one voter will vote for Kerry and at least one will not, then the conditional probability distribution of p given one's state of ignorance is the uniform distribution on the interval [0, 1]." seems highly improbable, unless Jaynes posthumously thought that the elctorate of the United States was infinite. --Henrygb 21:51, 19 Feb 2005 (UTC)
thread_title: Jaynes statement

message: Hello all, I found this article after spending quite some time working on the article a priori (statistics). I'm thinking that article should probably be integrated into this one, what do people think? The general article on a priori and a priori (math modeling) are both in need of work, and I thought I would engage some editors from this article into the work. Really, the math modelling article should be integrated as well. jugander (t) 22:02, 14 October 2006 (UTC)
replies: text: Yes I agree, it would make a more complete view on subject. Alfaisanomega (talk) 10:28, 7 December 2010 (UTC)
thread_title:  ''a priori'' 

message: "The Haldane prior has been criticized on the grounds that it yields an improper posterior distribution that puts 100% of the probability content at either p = 0 or at p = 1 if a finite sample of voters all favor the same candidate, even though mathematically the posterior probability is simply not defined and thus we cannot even speak of a probability content."
Shouldn't it be "puts 100% of the probability content NEAR either p = 0 or p = 1" because you get a continuous distribution and {0,1} has measure zero?  —Preceding unsigned comment added by JumpDiscont (talk • contribs) 17:17, 12 October 2009 (UTC)
replies: text: Such a posterior puts infinite measure on any set of the form (0, ε) no matter how small ε is, and finite measure on any set bounded away from 0.  Neither "near" nor "at" really captures this. Michael Hardy (talk) 18:29, 12 October 2009 (UTC)

text: Thanks to whoever is contributing to this article, it has helped me understand a lot.  I'm still confused on this point about the Haldane prior.  You can't integrate it from zero (because as you said it would be infinite) - so how can it make sense?  At least in the other distributions, I can integrate from zero to, say, .7, and I get the probability that p < .7.  What would be the probability that p < .7 in this case?  I think the paragraph above is trying to address it, but it's still baffling me. Maxsklar (talk) 18:38, 17 July 2010 (UTC)
thread_title:  Haldane prior 

message: I've found the APP acronym for a priori probability in some works, but I can't find a reference/source for this; sometimes the AAP is used instead. For example, looking for "a priori probability + app" in Google shows differences in usage. What do you think? 
Alfaisanomega (talk) 10:28, 7 December 2010 (UTC)
thread_title:  Acronym 

message: The term 'diffuse prior' links to this page but does not appear in the article.  I think this is the same idea as an uninformative prior, however because I'm not 100% sure I do not want to edit the article.  Would someone who knows more like to confirm or deny this?  — Preceding unsigned comment added by Mgwalker (talk • contribs) 01:05, 18 October 2011 (UTC)
thread_title:  Diffuse Prior 

message: Seems like a weasel word, replace by "unknown quantity"? Is it opposed to a "certain quantity"? The word uncertainty is used a lot in Bayesian statistics, but it's not always illuminating. Biker333 (talk) 11:14, 10 March 2013 (UTC)
thread_title:  What is an "uncertain quantity"? 

message: This section states that the beta prior with parameters (1,1) - which is uniform - is improper. This is wrong. The distribution has finite support and is finite everywhere, so can be integrated. It's a anyway a beta distribution, which can always be normalized.  — Preceding unsigned comment added by 92.74.64.12 (talk) 06:12, 7 July 2016 (UTC)
replies: text: Removed reference to beta(1,1) distribution. – Jt512 (talk) 20:12, 12 March 2017 (UTC)
thread_title:  Improper priors 

message: The first paragraph said:
: p is the probability distribution that would express one's uncertainty about p before some evidence is taken into account. 
It's circular to say that p expresses ones uncertainty about p.  In fact p expresses ones beliefs (which are typically uncertain) about some situation.  So, I'll change this to
: p is the probability distribution that would express one's beliefs about a situation before some evidence is taken into account. 
Feel free to improve it, but let's not say p expresses our uncertainty about p.
John Baez (talk) 18:10, 25 March 2015 (UTC)
thread_title:  Problems with first paragraph 

message: in the sentence
"Similarly, the prior probability of a random event or an uncertain proposition is the unconditional probability that is assigned before any relevant evidence is taken into account."
unconditional probability goes to marginal probabilities. 
My math is not strong as why I am reading this page to understand. so if they are the same please excuse me  — Preceding unsigned comment added by Therealmarcuschiu (talk • contribs) 18:42, 20 April 2019 (UTC)
thread_title:  Link Mistake? Unconditional Probability linked to Marginal Probability 

message: It's depressing to realize that the benighted notation used throughout this article is widespread in the world. Maybe I'll work on this article further. Michael Hardy (talk) 15:18, 16 June 2019 (UTC)
thread_title:  Abominable notation 

message: Could a more international example be found to explain weakly informative prior? I have no feeling at all for Fahrenheit. There must be some units where the US hasn't made up there own standard? 82.39.162.179 (talk) 11:04, 29 July 2020 (UTC)
thread_title:  Weakly informative prior 

message: The Short description was  which is 104 characters long and so the article was added to .
I have a "reasonable" understanding of stats, but found the article rather difficult to summarise in just a few words. In the end, I shortened the Short description to , which is 37 characters and so short enough. Is this new Short description "true" enough? — GhostInTheMachine talk to me 10:31, 24 February 2022 (UTC)
replies: text: I would write instead . It's 51 characters, so short enough. We shouldn't try to give a definition, just context. Tercer (talk) 12:50, 24 February 2022 (UTC)
thread_title:  Short description 

message: Would it make more sense to merge in Strong prior and have an expanded article on prior probability altogether? Silvestertaylor (talk) 22:38, 14 July 2023 (UTC)
replies: text: Indeed; a rather obvious case.  Klbrain (talk) 11:51, 27 December 2023 (UTC)
thread_title:  Proposed merge of [[Strong prior]] into [[Prior probability]]