When choosing an estimatorfor a statisitical parameter we are primarily interested insimplicity of calculation and the bias of the estimator.
The bias of a statisiticalparameter is the difference between the estimator for the parameterand the true value of the parameter. If the estimator for apopulation parameter
is
then![]()
We are usually interested inselecting the estimator with the smallest bias, since it will becloser to the actual value of the population parameter more often onaverage that any other estimator.
Suppose we are interested infinding an estimator for the population mean,
Wehave a choice of estimators:
![]()
where
and
areindividual measurements from the population
where
and
areindividual measurements from the population
Each of these estimators isunbiased, since
![]()

![]()
If the variance of
is
thenthe variance of
is

and the variance of
is

Of all these estimatorsfor![]()
hasthe smaller variance, so
isthe best estimator.