Developing a General Class of Ratio Estimator in Estimating The Population Means

The aim of this research is to present a general class of ratio estimators for estimating the population means under simple random sampling without replacement using the information on an auxiliary variable. The author has developed the estimator proposed by Cochran [1], Sisodia and Dwivedi [2], Upadhyaya and Singh [3], Singh and Tailor [4], Singh et al. [5], Yan and Tian [6], Subramani and Kumarpandiyan [7], Jerajuddin and Kishun [8], and Singh and Agnihotri [9], which was inspired by Singh and Agnihotri [9], Gupta and Yadav [10], and Sabo et al. [11]. In addition, the researcher has studied some important properties of the new general class of ratio estimators, such as Bias, Mean Squared Error (MSE), and Minimum Mean Squared Error (MMSE). The performance of the presented estimator is compared with relevant estimators using a theoretical approach and an application to real data on the basis of MSE and percent relative efficiencies (PRE) criterion. The results of this research showed that under the same situation, the presented estimator is more efficient than others.