🚀 go-pugleaf

In article <1992Aug14.231916.23479@magnus.acs.ohio-state.edu> regeorge@magnus.acs.ohio-state.edu (Robert E George) writes:
>
>More intuitively, if we take a very sample, we are less likely to get
>extreme values and so our notion of what the population variance is (note
>that I am not proposing some particular estimator) will be unrealistic.
>For instance, I give an exam to two students. Their scores are 67 and
>71. I think, "Gee, there's not a lot of variability in these scores."
>But then 8 more students take the exam:
>     60 78  100 38  50 88  99 39
>

I have a further question with regard to the negative biasness of
the sample variance estimate.

This and other posting indicate that there is a relationship between
sample size and and estimated variance (of the population) which is
positive and always an underestimate.  What is the limit, or point
at which an increasing sample size no longer improve the estimate
of populations variance?

Can this be tested by taking samples of sample (the later sample
being elevated to the status of population)?

cheers,
chris