Raul Miller wrote:

>
>> > I can determine \sum(X_i-\bar X)^2 for each of those
>> > potential sample cases (0, 0.5, 0.5, 0) and then
>> > average them.  For the fair coin, this average is
>> > 0.25.  For that unfair coin, I get 0.1875 for this
>> > average.
>>
>> This precisely illustrates the point.  The population variance is 3%8,
>> not 3%16.  You can see in this case that using denominator n=2
>> gives the wrong answer, using denominator n-1 gives the correct
>> answer.
>
> I am not sure this is a valid point.

Why?  This shows that the method you are using does not produce an
unbiased estimator of variance, but mine does.

>
> See
> http://en.wikipedia.org/wiki/Standard_deviation#Estimating_population_standard_deviation_from_sample_standard_deviation
> as an example treatment which seems to conflict with the assertions
> you have advanced in this last paragraph.
>
This gives a biased estimator.

> As I understand the wiki write up, even if you consider denominator
> n=1 as valid for samples which do not represent the population,
> you must still use denominator n=2 when you are dealing with
> the population distribution.

What is a sample which does not represent the population?

Bset wishes,

John

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