Enhanced Ratio-Type Estimator for Finite Population Mean using Auxiliary Variable in Simple Random Sampling

Abstract

In this paper, a ratio-type estimator of finite population mean in simple random sampling without replacement by using information on an auxiliary variable has been proposed. The proposed estimator was obtained by using the strategy of power transformation and incorporated the unknown weight (). The objective of this study is to develop a new ratio estimator that provide better precision of estimation of population mean. The properties such as bias and mean square error (MSE) of the proposed estimator are derived and tested using four real data sets. The results of the empirical study revealed that the proposed ratio type estimator performed better than the existing estimators considered in the study. Therefore, the proposed estimator is more efficient than the existing estimators based on the criteria of mean square error and percent relative efficiency.