Improved Ratio Estimators of Variance Based on Robust Measures

In this study, we develop some new estimators for estimating the population variance by utilizing the information on midrange and inter decile range of an auxiliary variable. A general class of estimators is also suggested. The derivations of the bias and the mean squared error are presented. Conditions are determined to verify the efficiency of the proposed estimators over existing estimators considered in this study. An Empirical study is also provided for illustration and verification. Moreover, a robust study is also carried out to evaluate the performance of proposed estimators as compared to existing estimators in case of extreme values. From the theoretical and empirical study, it is found that the suggested estimators perform more efficiently as compared to the existing estimators considered in this study.