It does. Calculate the variance for both of them and use the one that is smaller. Note that we usually cannot get rid of the term in the denominator of the variance, but we can decrease the coefficients and such.
For a Uniform
The Maximum Likelyhodd Estimator of =
Also, the sufficient statistic for is
and E[X] =
Then the estimators of are found out as
=
and
Which one is the better estimator? What is the process to find it?
I am wondering if the answer involves calcuating the variance.
I think it is important to notice that the second moment brings in the This means our sample size is always going to effect our dispersion.
Now to finish the variance of the second estimator multiply by all that stuffs.
One of your estimators was found by MLE and the other by the method of moments. Which one is better? Why?