GENERALIZED FAMILY OF ESTIMATORS VIA TWO AUXILIARY VARIABLES FOR POPULATION VARIANCE

The variance estimators have been recommended in sampling literature by many authors. It is highly popular to use auxiliary variable information to achieve more effective estimators. Moreover, the variance estimators have been studied using the information of two auxiliary variables in recent years. In this paper, we suggest three families of estimators using the information of two auxiliary variables for the estimation of the population variance in the simple random sampling method. The asymptotic expressions for the mean squared error (MSE) of the suggested family of estimators have been derived up to the first order of approximation. We show that the suggested estimators are more efficient than the classical estimators and the existing estimators in Literature under the determined conditions obtained in theory. We also support the performances of the suggested estimators with the aid of two real population data sets.