Standard Deviation of a sample of a population's means

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2^Oscar
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Hey guys,

Just a question which has been puzzling me for some time.

I am told that means of samples of a population can be normally distributed with mean of [tex]\mu[/tex] and with standard deviation of [tex]\sigma[/tex]/[tex]\sqrt{}[/tex]n

Can someone please explain to me how the standard deviation is derived or is it ismply as a result of experimentation?

Thanks,
Oscar
 
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It is derived. The given result follows if the population is normal.
 
The mean is

[tex] \overline X = \frac{\sum X}{n}[/tex]

If all of the [tex]X[/tex] variables are independent, and identically distributed, then

[tex] Var[X] = Var\left(\frac{\sum X}n\right) = \frac 1 {n^2} \sum Var(X) = \frac{n\sigma^2}{n^2} = \frac{\sigma} n[/tex]

so the standard deviation is as you state.

If the [tex]X[/tex] values are themselves normally distributed, then the mean is as well (linear combinations of normally distributed normal random variables are normal)

If the [tex]X[/tex] values are not normally distributed, the distribution of [tex]\overline X[/tex] is approximately normal if certain conditions are satisfied.
 
statdad said:
[tex] Var[X] = Var\left(\frac{\sum X}n\right) = \frac 1 {n^2} \sum Var(X) = \frac{n\sigma^2}{n^2} = \frac{\sigma} n[/tex]

You forgot the root in the denominator.

CS
 
stewartcs said:
You forgot the root in the denominator.

CS
No, actually I forgot the square in the numerator, since I was writing out the variance. :frown:
Still a stupid mistake on my part.

The variance is

[tex] \frac{\sigma^2} n[/tex]

so the standard deviation is

[tex] \frac{\sigma}{\sqrt n}[/tex]
 
statdad said:
No, actually I forgot the square in the numerator, since I was writing out the variance. :frown:
Still a stupid mistake on my part.

The variance is

[tex] \frac{\sigma^2} n[/tex]

so the standard deviation is

[tex] \frac{\sigma}{\sqrt n}[/tex]

Sorry...it appeared as if you were answering the OP's question about the standard deviation directly which is why I assumed you had finished the derivation all the way out to the standard deviation and not just the variance.

CS
 
stewartcs; there is no need for you to apologize and I certainly did not mean to imply (in my earlier post) that there was. I am sorry if it seemed that way.
 
Hey guys,

Thanks very much for showing me the derivation - it has helped make things a lot clearer :)

Thanks again,

Oscar