Sharif University of Technology Scientia Iranica 1026-3098 29 4 2022 08 01 A novel improved class of ratio-product type exponential estimators of population variance 2115 2133 21998 10.24200/sci.2020.53481.3260 EN F. Naz School of Mathematical Sciences, Institute of Statistics, Zhejiang University, Hangzhou 310058, China T. Nawaz - Department of Statistics, Faculty of Physical Sciences, Government College University Faisalabad, Allama Iqbal Road, Faisalabad 38000, Pakistan. - School of Mathematical Sciences, Shanghai Jiao Tong University, Minhang Campus, 800 Dongchuan Road, Shanghai 200240, China. M. Abid Department of Statistics, Faculty of Physical Sciences, Government College University Faisalabad, Allama Iqbal Road, Faisalabad 38000, Pakistan T. Pang School of Mathematical Sciences, Institute of Statistics, Zhejiang University, Hangzhou 310058, China Journal Article 2019 05 04 Several auxiliary information-based estimators of the population variance are available in the existing literature of survey sampling. Mostly, these estimators are based on conventional dispersion measures of the auxiliary variable. In this study, a generalized class of ratio-product type exponential estimators of the population variance is proposed which integrates the auxiliary information on non-conventional dispersion measures under simple random sampling in the ratio-type exponential class of estimators. The performance of the proposed estimators is compared, theoretically and numerically, with the several existing estimators of the population variance. It is established that the proposed class of estimators outperforms the existing estimators in terms of the lower mean square and relative root mean square errors. Moreover, the percentage relative efficiency of the proposed estimators is much higher as compared to their counterparts. https://scientiairanica.sharif.edu/article_21998_897ae146b93d093386a4155940e5a18d.pdf