Raul Miller wrote:
> On 6/29/07, John Randall <[EMAIL PROTECTED]> wrote:

>> Why?  This shows that the method you are using does not produce an
>> unbiased estimator of variance, but mine does.
>
> This terminology "biased" vs. "unbiased" does not appear to be relevant
> when talking about population variance.
>

True, but it does with estimators: an unbiased estimator of a parameter is
a statistic whose expected value is that parameter.



>> What is a sample which does not represent the population?
>
> The issue seems to be completeness.
>
> The "unbiased" estimator traditionally gets used when dealing with
> variance for a sample which is not identical to the population.  In
> other words, if there's any possibility that the distribution of the
> sample is different from the distribution of the population, it seems
> to be traditional to use the "unbiased estimator" (n/n-1 when determining
> RMS deviation rather than the "biased estimator" of 1 when determining
> RMS deviation).


I don't understand this.  A random sample is defined to be a list of
independent random variables each with the same distribution as the
population.  What does "a sample which is not identical to the population"
mean?

Best wishes,

John


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