An efficient exponential estimator of the mean under stratified random sampling

Stratification of population is a probability sampling design used to increase the precision of estimation. An efficient exponential ratio estimator allows estimating the population mean in stratified random sampling using an auxiliary variable. Its expected bias, expected mean square error, and minimum mean square error are expressed. The conditions for which the estimator is more efficient are obtained. The proposed estimators under stratified random sampling have a lower mean square error than the ratio and the exponential estimators.

Automated summary

Population stratification aims to increase the precision of estimation, using an efficient exponential ratio estimator to estimate the population mean in stratified random sampling can reduce bias and mean square error. The proposed estimators perform more efficiently under stratified random sampling, with lower mean square error compared to ratio and exponential estimators.