>> x=randn(300,1);
>> dfittool(x)
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%Click "New Fit..." and "Apply",then it returns
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%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.