Timeline for Tightest bounds on sample variance given sample size, mean, minimum, and maximum
Current License: CC BY-SA 4.0
11 events
| when toggle format | what | by | license | comment | |
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| Dec 13, 2022 at 13:50 | comment | added | Henry.L | Sure. I think so, but also more restrictive. | |
| Dec 13, 2022 at 9:18 | comment | added | equaeghe | @Henry.L: m (minimum) and M (maximum) are bounds, so their results hold. That means that the extra assumption I'm making is that the minimum and maximum are known (that is explicit). So then given that, are my bounds tighter? | |
| Dec 12, 2022 at 6:54 | comment | added | Henry.L | @equaeghe The theorems you cited (Davies-Nagy) does not assume that $m=x_{(1)}$ nor $M=x_{(n)}$, they just say bounded variables. You are putting additional assumptions and claim a different result, so it is difficult to say what you mean by "tighter"? | |
| May 7, 2018 at 12:26 | history | edited | equaeghe | CC BY-SA 4.0 |
clarify that I am interested in general real-valued samples, not discrete ones
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| May 7, 2018 at 11:50 | history | edited | equaeghe | CC BY-SA 4.0 |
clarified role of sample size in context
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| May 6, 2018 at 10:21 | history | tweeted | twitter.com/StackStats/status/993073346668564481 | ||
| May 4, 2018 at 20:10 | answer | added | Steve Kass | timeline score: 1 | |
| Dec 7, 2017 at 21:32 | comment | added | equaeghe | $\kappa$ is defined implicitly by the next-to-last displayed equation: $m\leq\kappa=-(n_mm+n_MM)\leq M$. | |
| Dec 7, 2017 at 16:31 | comment | added | whuber♦ | I must be having problems reading today, because despite scanning this question many times I cannot find a definition of "$\kappa$" anywhere: exactly how is it determined by $M, m,n,$ and $\mu$ alone? BTW, the comments to the question at stats.stackexchange.com/questions/142655 might be of some interest concerning the upper bound. | |
| Dec 6, 2017 at 22:41 | review | First posts | |||
| Dec 6, 2017 at 23:32 | |||||
| Dec 6, 2017 at 22:37 | history | asked | equaeghe | CC BY-SA 3.0 |