Thread Subject: Using normfit with weighted data values

Hi All,
I’m trying to use "normfit" to estimate the 95% confidence
limit for the mean of a series of normally distributed
experimental data points. Each point has an individual
weight according to uncertainties in the experimental
routine and I would like to take them into account in the
calculation. From looking at the code of normfit I can see
that the 95% confidence limit for the mean (muhat) is
derived from the standard deviation (sigmahat) and the
number of data points (m) in the following way:

Lower_limit=muhat+tinv(0.025,m-1)*sqrt(sigmahat.^2/n);
Upper_limit=muhat-tinv(0.025,m-1)*sqrt(sigmahat.^2/n);

So (finally) here is my question. If I simply use a weighted
mean and weighted standard deviation in the formulas above
will that provide me with a correctly weighted 95%
confidence interval, or will the weights play some role in
also modifying the value of m?

thanks,

Dave