>> x=randn(300,1);
>> dfittool(x)
%Click "New Fit..." and "Apply",then it returns
%The Results pane displays the mean and standard deviation of the normal distribution that best fits x, as shown in follow
Distribution: Normal
Log likelihood: -400.751
Domain: -Inf < y < Inf
Mean: -0.0170083
Variance: 0.849699
Parameter Estimate Std. Err.
mu -0.0170083 0.0532196
sigma 0.921791 0.0377264
Estimated covariance of parameter estimates:
mu sigma
mu 0.00283233 5.16186e-020
sigma 5.16186e-020 0.00142328
%Get help by typing "doc disttool" at the command line.