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Journal of Probability and Statistics
Volume 2014, Article ID 360549, 8 pages
Research Article

On Improving Ratio/Product Estimator by Ratio/Product-cum-Mean-per-Unit Estimator Targeting More Efficient Use of Auxiliary Information

Department of Mathematics and Statistics, Faculty of Science and Technology, The University of the West Indies St Augustine, St. Augustine, Trinidad and Tobago

Received 2 August 2014; Accepted 28 August 2014; Published 23 September 2014

Academic Editor: Aera Thavaneswaran

Copyright © 2014 Angela Shirley et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


To achieve a more efficient use of auxiliary information we propose single-parameter ratio/product-cum-mean-per-unit estimators for a finite population mean in a simple random sample without replacement when the magnitude of the correlation coefficient is not very high (less than or equal to 0.7). The first order large sample approximation to the bias and the mean square error of our proposed estimators are obtained. We use simulation to compare our estimators with the well-known sample mean, ratio, and product estimators, as well as the classical linear regression estimator for efficient use of auxiliary information. The results are conforming to our motivating aim behind our proposition.