Sample mean variance and division by (n-1)

AI Thread Summary
When calculating sample mean variance, division by n is appropriate if the population mean is known, as it reflects the variance of the sample mean rather than the population variance. In contrast, when estimating population variance from a sample where the population mean is unknown, division by (n-1) is used to account for bias. The difference between dividing by n and (n-1) diminishes with larger sample sizes. Understanding this distinction is crucial for accurate statistical analysis. Thus, the method of division depends on whether the population mean is known or estimated.
monsmatglad
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Hi. i wonder how come one doesn't divide with (n-1) when finding the sample mean variance.


Homework Equations



Shouldn't I divide with n -1 since it is samples i am dealing with?

The Attempt at a Solution



I don't really have any idea as to why the book uses n. I have googled but could not find anything. I can use the result i find when following the procedure in the book, but i don't understand why the sample mean variance is not treated as a regular sample from a population - which in previous chapters would mean division by n -1 when finding the "regular" variance.

Mons
 
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Is this a situation where n is large? The difference between dividing by n and dividing by n-1 would be small for large n.
 
monsmatglad said:
Hi. i wonder how come one doesn't divide with (n-1) when finding the sample mean variance.


Homework Equations



Shouldn't I divide with n -1 since it is samples i am dealing with?

The Attempt at a Solution



I don't really have any idea as to why the book uses n. I have googled but could not find anything. I can use the result i find when following the procedure in the book, but i don't understand why the sample mean variance is not treated as a regular sample from a population - which in previous chapters would mean division by n -1 when finding the "regular" variance.

Mons

You divide by (n-1) when estimating the population variance, when the population mean is also unknown and must be estimated, too. If you *know* the population mean exactly (so don't need to estimate it) you would divide by n when estimating variance. However, when estimating the variance of a *sample mean*, you divide the estimated population variance by n, because Var(sample mean) = (Population variance)/n, exactly. When you estimate Population variance, you still divide by n here (although you divided by n-1 when estimating population variance---in effect, you have divided by n*(n-1)).

RGV
 
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