ABSTRACT

Statistical inference is basically drawing of valid statistical conclusions about the population characteristics on the basis of a sample drawn from the population in a systematic manner. Two important problems in statistical inference are: estimation and testing of hypothesis. A point estimator is a sample statistic, which is used to estimate a population parameter. A particular numerical value of the point estimator is known as the estimate of the population parameter. ‘Completeness’ of a statistic, in the context of a given probability family, is a property of the estimator that guarantees that the unbiased estimator is unique which may be written as a function of a sufficient statistic; this estimator is then automatically the Uniform Minimum Variance Unbiased Estimator. The method of maximum likelihood is widely regarded as the best general method of finding estimators. Moment method is easy to employ and usually provides consistent estimators for respective parameters.