> What I'd like to do is overlay the actual normal Gaussian curve to
> show how it is approaching it. Maybe this is more of a question of
> the math then of Matlab, but I'm wondering if there is a function in
> the statistics toolbox that will help me with this?
There is: NORMPDF gives you the density of a normal distribution, you just have
to scale it properly so that it integrates to the same thing as the histogram's
envelope. The function below does this. Hope it helps.
You might find that QQPLOT is a better way of doing what you want. It's
sometimes hard to judge how "normal" a histogram is, and a qqplot gives you a
much easier way to see skewness and kurtosis relative to the normal  just look
at the ends of the plot.
 Peter Perkins
The MathWorks, Inc.
function parmhat = normplot(x, params)
%NORMPLOT Plot fitted against observed for normally distributed data.
% NORMPLOT(X) fits a normal distribution to X, and plots the fitted pdf
% overlayed on a histogram of X.
%
% NORMPLOT(X, PARAMS) plots the pdf based on the values in PARAMS.
%
% See also NORMFIT, NORMLIKE, NORMPDF.
if nargin < 2
[mu,sigma] = normfit(x);
else
mu = params(1); sigma = params(2);
end
parmhat = [mu, sigma];
xmin = min(x); xmax = max(x); xrange = range(x);
binw = xrange / 50;
edges = xmin + binw*(0:50);
n = histc(x, edges);
bar(edges, n, 'histc', 'w');
hold on
xx = xmin:(xrange/1000):xmax;
plot(xx, binw*length(x)*normpdf(xx,mu,sigma), 'b');
title('Normal Fit');
legend('Fitted PDF', 'Observed Data');
hold off
