AN EFFICIENT EXPONENTIAL TYPE ESTIMATOR FOR ESTIMATING FINITE POPULATION MEAN UNDER SIMPLE RANDOM SAMPLING.

In this paper, an improved exponential type estimator for estimating the population mean is proposed under simple random sampling scheme. The proposed estimator was obtained by combination of conventional product and exponential-type ratio estimators with aim of obtaining estimator with higher efficiency. The bias and mean squared error (MSE) of the proposed estimator were obtained up to the first order of approximation using binomial and exponential expansion techniques and the optimum value of the unknown constant of the estimator was derived by means of partially differentiating the mean squared error and equating to zero. Also, the conditions under which the proposed estimator is more efficient than the conventional estimators in the literature are established. An empirical study was carried out to support the fact that the proposed estimator is better than the existing ones, as the proposed estimator has a minimum mean squared error at the optimum value of the unknown constant and has higher percentage relative efficiency (PRE). This implies that the proposed estimator is more efficient than the conventional product and exponential-type ratio estimators considered in the study. [ABSTRACT FROM AUTHOR]