Improved Estimation of Finite Population Variance Using Dual Supplementary Information under Stratified Random Sampling

In this article, we propose an improved estimator for finite population variance based on stratified sampling by using the auxiliary variable as well rank of variable. Expressions bias and mean square error estimators are derived up to first order approximation. Four real data sets used measure performances estimators. Moreover, a simulation study is also conducted observe efficiency proposed estimator. The theoretical numerical results show that under random more efficient compared existing