Talk:Binomial proportion confidence interval

message: In the section "Bracketing the confidence interval" I don't think the statement " z is the 1-⍺/2 quantile of a standard normal distribution (i.e., the probit) corresponding to the target error rate ⍺" is true for the Michael Short formula.
It should just be the 1-⍺ quantile, and probably use another symbol than z, since z is already defined above in the Wald formula.
Documentation: Short's formulas are found in his cited article p. 4188 and 4189, z^2 is here called C5 and defined as C5 = Φ^(-1)(R), where R is just the confidence level. My claim is also supported by the example he goes through on p. 4189 using a confidence level of 95% which yields C5 = 2.706, which would be C5 = 3.841 if using the 1-⍺/2 quantile.  — Preceding unsigned comment added by 185.45.22.138 (talk) 11:04, 20 September 2023 (UTC)
replies: text: Please have a look at the German WP article on this topic. It includes an example and tries to illustrate the intervals and the coverage probabilities. -- KurtSchwitters (talk) 09:17, 4 February 2011 (UTC)
thread_title:  suggestions for improvement 

message: The above discussion suggests that there may be a good reason to expand the scope of ths article to become "Interval estimation for binomial proportions" and to allow an equal footing in the article for credible intervals, with distinctions being made where appropriate. But that might just get too confusing. Perhaps there could be a separate article called "Binomial proportion crediible interval". Melcombe (talk) 10:06, 15 February 2011 (UTC)
replies: text: Extending the scope seems a reasonable idea to me, especially as one confidence interval with reasonable frequentist properties that's not covered here at present is the credible interval resulting from a Jeffreys prior, so there's some overlap. The theory of credible intervals for a binomial proportion is simpler than that of confidence intervals (once you've decided on your prior), so it shouldn't take too long to explain. Much of the mathematical basis is already present at conjugate prior#Example but that doesn't mention credible intervals, while the credible interval article lacks any examples, so this could be a nice illustration. I'm not volunteering to write it though! Qwfp (talk) 11:05, 15 February 2011 (UTC)
replies: text: I have just added a section Binomial proportion confidence interval#Jeffreys interval, however. If someone wishes to edit and extend it to include informative priors and thus 'fully' Bayesian credible intervals, that's fine with me. Qwfp (talk) 15:45, 15 February 2011 (UTC)
thread_title: Extension of scope

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thread_title:  External links modified 

message: The article states the Wilson score is asymmetric. This is sourced to an article from Journal of Quantitative Linguistics. This may be a stupid question but how exactly is the Wilson score asymmetric? The formula for the Wilson score confidence interval is:
Point +/- stuff
It’s “+/-“ the same thing (“stuff”). Adding and subtracting the same thing to a point estimate gives a symmetric CI. 
I think the word “asymmetric” here is being misunderstood here and used in the wrong way. The Wilson Score CI may be asymmetric in some other sense (density within the interval? That doesn’t make sense either though) but here the wording appears to be be confused. 
Can anyone clarify?  Volunteer Marek  00:24, 1 January 2022 (UTC)
thread_title:  Wilson score asymmetric