An improved Exponential-Type Estimator for Finite Population Variance Using Transformation of Variables

In this article we have proposed an improved exponential-type for estimating the unknown population variance of the study variable, using transformation on both the study as well as on the auxiliary variable. The properties of the suggested estimator have been discussed up to first order of approximation. We also have derived some efficiency comparison conditions under which the proposed variance estimator performed better than the usual unbiased estimator, traditional ratio estimator and [1] estimators. Theoretical efficiency conditions are verified numerically by taking some real data sets taken from the literature, with a result in increasing the efficiency