Enhanced Logarithmic-Type Estimators for Estimation ofPopulation Variance Under Simple Random SamplingFramework: Computational Analysis andSimulation Evidence

Survey sampling continues to play a pivotal role in modern statistical research, offering a ‎efficient means of estimating population parameters without requiring a complete enumeration. ‎However, practical data collection frequently involves extreme or atypical observations that, if ‎overlooked, can distort estimation accuracy and lead to biased conclusions. The former research ‎primarily focuses on use of auxiliary information to estimate the population parameters of main ‎variable. The class of estimators suggested in this category one ratio type estimators, product type ‎estimators and regression type estimators. Later, Bahl and Tuteja (1991) suggested a new class of ‎exponential and product estimators. Recent advancements have introduced logarithmic-type ‎estimators, but their statistical properties remain only partially explored. Recognizing this ‎challenge, the present study proposes a refined logarithmic-type estimator for finite population ‎variance within the framework of simple random sampling without replacement (SRSWOR). The ‎estimator incorporates auxiliary information to improve the precision and stability of variance ‎estimation. Theoretical properties, including bias and mean squared error (MSE), are derived up ‎to the first order of approximation, ensuring a rigorous analytical foundation. To assess its ‎performance, comparative and simulation-based analyses are carried out against several existing ‎estimators. The findings reveal that the proposed estimator consistently produces lower MSE ‎values and exhibits greater robustness. These results confirm both the theoretical and empirical ‎superiority of the proposed approach. Overall, the study contributes to the growing body of ‎literature on efficient estimation techniques by presenting a more accurate and reliable alternative ‎for population variance estimation in survey sampling and their applications‎.