Improved Estimation of Finite Population Variance in Stratified Random Sampling

Abstract

This paper focuses on the formulation of estimators for the finite population variance, leveraging information on the first and second raw moments of the study variable under stratified random sampling. Furthermore, we introduce combined and separate estimators that utilize supplementary information on a study variable along with auxiliary variable to estimate the population variance. The comparative evaluation of the proposed estimators against existing one is conducted based on absolute bias and relative efficiency. Both simulated and empirical studies indicate that the newly proposed estimators demonstrate potential superiority over their existing counterparts.