(untitled) (International Journal of Food and Nutritional Sciences, 2022)
In this research paper, we conducted a thorough examination of various existing ratio estimators utilizing a single auxiliary variable by analyzing real population data. The study systematically compares their efficiencies, employing a robust methodology. The experimental setup involves the selection of a sample from a real population, utilizing the simple random sampling without replacement method. Unlike simulations, our approach involves direct application to actual population data, enhancing the external validity of the findings. We evaluate the performance of different ratio estimators concerning bias, mean square error, providing valuable insights into their real-world applicability. The results revealed that, the estimator t13 is the most efficient and t2 is the least efficient estimator of population mean. This comprehensive analysis contributes valuable insights into the comparative efficiency and performance characteristics of various ratio estimators under the given conditions, providing a detailed understanding of their applicability in estimating population parameters.