ABSTRACT

An estimator is a function of sample values, whereas an estimate is a numerical value of the estimator. An estimate may be a single statistic, which is called point estimates or a range with attached probabilities called interval estimates or confidence intervals. A consistent estimator gets increasingly better as the sample size increases. For example, the sample mean and the median are consistent estimators of their respective parameters. An efficient estimator is one for which the standard error is small. A resistant estimator is not affected too much by the presence of extreme values or the outliers in the data. The estimation of confidence interval is important since the investigator can never estimate the exact values of the parameter with certainty. The sampling variance decreases with increase in the sample size; but at the same time, the cost of the survey also increases.