ABSTRACT
This chapter reviews the several major statistical properties that estimators should ideally possess. The statistics give information about the average value of the sample and tell the extent to which the sample observations deviate from the mean value. Consistency is important since it gives improved estimates with increasing sample size. Hence the probability distribution of the estimator will tend to become more and more concentrated on the population parameter with increases in the sample size. The normal distribution is probably the best-known and most widely used distribution in statistics. The critical region is then identified from statistical tables giving the 5% points of the distribution. If the test statistic lies within the critical region the null hypothesis is rejected and the alternative hypothesis is accepted. Conversely, if the test statistic lies outside the critical region, in the so-called acceptance region, the null hypothesis is accepted and the alternative hypothesis is rejected.
