An Alternative Hybrid Estimator of Finite Population Mean in Simple Random Sampling
T. Uba *
Department of Mathematics/ Statistics/ Computer Science, Joseph Sarwuan Tarka University, Makurdi, Nigeria.
A. J. Ikughur
Department of Mathematics/ Statistics/ Computer Science, Joseph Sarwuan Tarka University, Makurdi, Nigeria.
S. C. Nwaosu
Department of Mathematics/ Statistics/ Computer Science, Joseph Sarwuan Tarka University, Makurdi, Nigeria.
*Author to whom correspondence should be addressed.
Abstract
In this paper, we propose an alternative hybrid estimator of finite population mean in simple random sampling without replacement (SRSWOR). This proposed estimator is a modification of Rashid et al. [1] estimator. The expressions for the bias and Mean Square Error (MSE) of the estimator are derived. A comprehensive simulation study to show the efficacy of the estimator as compared to conventional estimators using Coefficient of Variation as a performance measure. The results are also supported with empirical illustrations using real life data which have shown that the proposed estimator was more efficient than almost all the existing estimators considered in this study.
Keywords: Auxiliary variable, hybrid estimators, mean square error, ratio estimators, regression estimators.