Timeline for Why is binomial variance calculated as $p(1-p) / (n -1)$?
Current License: CC BY-SA 4.0
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Apr 28, 2022 at 23:11 | history | edited | Glen_b | CC BY-SA 4.0 |
added 57 characters in body
|
| Sep 24, 2021 at 6:56 | comment | added | Glen_b |
The sample variance is not p(1-p) .... > var(rep(c(0,1),c(4,6))) .... [1] 0.2666667
|
|
| Nov 3, 2020 at 10:50 | comment | added | Hernan | I don't think this is correct. The variance of sample is p(1-p) and does not involve n. The variance of the estimated proportion p is p(1-p)/n in the same way that the variance of the estimated mean is s^2 / n | |
| Aug 16, 2018 at 18:15 | history | edited | Glen_b | CC BY-SA 4.0 |
added 121 characters in body
|
| Dec 21, 2017 at 23:13 | vote | accept | disc0dancer | ||
| Apr 13, 2017 at 12:44 | history | edited | CommunityBot |
replaced http://stats.stackexchange.com/ with https://stats.stackexchange.com/
|
|
| Jan 23, 2017 at 10:15 | history | edited | Glen_b | CC BY-SA 3.0 |
added 345 characters in body
|
| Jan 23, 2017 at 8:35 | comment | added | Markus Loecher | Great point on the "double standard" in bias acceptance for binomial variance compared to "regular" variance. None of the (many) introductory stats textbooks I use even mentions the p*(1-p)/(n-1) form. One possible explanation is the requirement of a high sample size for proportions in the first place. | |
| Jan 23, 2014 at 0:08 | history | edited | Glen_b | CC BY-SA 3.0 |
added 9 characters in body
|
| Jan 22, 2014 at 22:46 | history | answered | Glen_b | CC BY-SA 3.0 |