Sharif University of Technology Scientia Iranica 1026-3098 27 4 2020 08 01 Enhancing efficiency of ratio-type estimators of population variance by a combination of information on robust location measures 2040 2056 21219 10.24200/sci.2019.5633.1385 EN F. Naz Department of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027, People’s Republic of China 0000-0001-5837-1072 M. Abid Faculty of Physical Sciences, Department of Statistics, Government College University Faisalabad, Pakistan T. Nawaz Faculty of Physical Sciences, Department of Statistics, Government College University Faisalabad, Pakistan. ;School of Mathematical Sciences, Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China. 0000-0003-0609-2084 T. Pang Department of Mathematics, Institute of Statistics, Zhejiang University, Hangzhou 310027, People’s Republic of China. Journal Article 2017 11 22 Numerous ratio-type estimators of the population variance are proposed in the existing literature based on different characteristics of the study as well as the auxiliary variable. However, mostly the existing estimators are based on the conventional measures of the population characteristics and their efficiency is dubious in the presence of outliers in the data. This study presents improved families of variance estimators under simple random sampling without replacement assuming that the information on some robust non-conventional location parameters of the auxiliary variable is known besides the usual conventional parameters. The bias and mean square error of the proposed families of estimators are obtained and the efficiency conditions are derived mathematically. The theoretical results are supplemented with the numerical illustrations by using real datasets which indicates the supremacy of the suggested families of estimators. https://scientiairanica.sharif.edu/article_21219_67ec81b79e603104769e55b6febbe4f1.pdf