Characteristics of Estimators
Next section: Estimating variance
Statistics are used to estimate
parameters. Three important attributes of statistics as estimators
are covered in this text:
unbiasedness,
consistency, and
relative efficiency.
Most
statistics you will see in this text are unbiased estimates of the parameter
they estimate. For example, the
sample mean, M,
is an unbiased estimate of the
population mean, μ.
All
statistics covered will be consistent estimators. It is hard to imagine
a reasonably-chosen statistic that is not consistent.
When more than one
statistic can be used to estimate a parameter, one will naturally be more
efficient than the other(s). In general the relative efficiency of two
statistics differs depending on the shape of the distribution of the numbers
in the population. Statistics that minimize the sum of squared deviations
such as the
mean are generally the most efficient
estimators for
normal distributions but may
not be for highly
skewed distributions.
Next section: Estimating variance