A statistic
is said to be an unbiased estimate of a given parameter when the mean of the sampling
distribution of that statistic can be shown to be equal to the parameter being
estimated.
For example, the mean of a sample is an unbiased estimated of the
mean of the population from which the sample was drawn.
s-square calculated
on a sample is an unbiased estimate of the variance of the population from which
the sample was drawn.
s-square divided by n (the size of the sample) is an
unbiased estimate of the variance of the sampling distribution of means for random
samples of size n and the square root of this quantity is called the standard
error of the mean. It is a commonly used index of the error entailed in estimating
a population mean based on the information in a random sample of size n.