[EMAIL PROTECTED] (Xiao Li) wrote in message 
news:<[EMAIL PROTECTED]>...
> Let N be the population size.  Let p denote the proportion of this
> population with a certain characteristic (ie. has diabetes, divorced,
> homosexual, etc.)  Let's say we are trying to estimate p using a
> sample of size n.  So we collect our sample and calculate p^ to be the
> proportion of elements in our sample with our characteristic of
> interest.  Then we calculate the standard of deviation of p^ (also
> known as the standard error) because it gives us an idea of how close
> our sample proportion is to the real proportion.
> 
> Now, my statistics textbook says the standard of deviation is given by
>  SD(p^) = root[(p^(1-p^))/n] when sampling with replacement or when
> the sample size is significantly smaller than the population size.
> 
> My question is why isn't there a N variable in our equation for
> SD(p^)?  According to this formula, if we are trying to figure out the
> proportion of people with diabetes in Berkeley, California with sample
> size n, we would get the same standard of error as if we are trying to
> figure out the proportion of people with diabetes in the world with
> sample size n.  (In the former, the N is a lot smaller than in the
> later).

For a sample of size n, drawn without replacement from a population of
size N in which the variance is V, the sampling variance of the sample
mean is (V/n)(N-n)/(N-1). If N >> n then V/n is often close enough.
.
.
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