Given a sample from apopulation, we can estimate the mean of the population from![]()
As the sample sizeincreases, the variance of
decreases.This property makes
a useful estimator for the population mean,
sinceby increasing the sample size n, we can reduce the variance of
If
isalso an unbiased estimator for the population mean
then
isa consistent estimator for![]()
If an estimator
fora population parameter
hasthe properties
and
asthe sample size for calculating
tendsto infinity, then
isa consistent estimator for![]()
The sample mean
isan unbiased estimator for the population mean
since
Since also, if the variance of the population is
andthe mean is found from a sample of size n using
then
and
isa consistent estimator for![]()
Similarly, for a binomialdistribution with proportion
fromwhich a sample of size
istaken, and we record the number of success as
andthe proportion as
theproportion of 'successes' is expected to be
![]()
The variance of
is
![]()
The variance of
tendsto zero as n tends to infinity so
isa consistent estimator for![]()