_____________________________________ *Corresponding author: E-mail: babington4u@gmail.com, ishaq.o.o@kustwudil.edu.ng; Asian Journal of Probability and Statistics 13(3): 13-29, 2021; Article no.AJPAS.63920 ISSN: 2582-0230 _______________________________________________________________________________________________________________________________________ Difference-Cum-Ratio Estimators for Estimating Finite Population Coefficient of Variation in Simple Random Sampling A. Audu 1 , M. A. Yunusa 1 , O. O. Ishaq 2* , M. K. Lawal 3 , A. Rashida 4 , A. H. Muhammad 4 , A. B. Bello 4 , M. U. Hairullahi 4 and J. O. Muili 1 1 Department of Mathematics, Usmanu Danfodiyo University Sokoto, Nigeria. 2 Department of Statistics, Kano University of Science and Technology, Nigeria. 3 Academic Planning Unit, Federal Polytechnic Bida, Nigeria. 4 State College of Basic and Remedial Studies, Sokoto, Nigeria. Authors’ contributions This work was carried out in collaboration among all authors. Authors AA, MAY and OOI designed the study, performed the statistical analysis, wrote the protocol and wrote the first draft of the manuscript. Authors AR and JOM managed the analyses of the study. Authors MKL, AHM, ABB and MUH managed the literature searches. All authors read and approved the final manuscript. Article Information DOI: 10.9734/AJPAS/2021/v13i330308 Editor(s): (1) Dr. S. M. Aqil Burney, University of Karachi, Pakistan. Reviewers: (1) Jacob Oketch Okungu, Meru University of Science and Technology, Kenya. (2) Kumarapandiyan G, University of Madras, India. Complete Peer review History: http://www.sdiarticle4.com/review-history/63920 Received: 25 October 2020 Accepted: 30 December 2020 Published: 09 June 2021 __________________________________________________________________________________ Abstract In this paper, three difference-cum-ratio estimators for estimating finite population coefficient of variation of the study variable using known population mean, population variance and population coefficient of variation of auxiliary variable were suggested. The biases and mean square errors (MSEs) of the proposed estimators were obtained. The relative performance of the proposed estimators with respect to that of some existing estimators were assessed using two populations’ information. The results showed that the proposed estimators were more efficient than the usual unbiased, ratio type, exponential ratio-type, difference-type and other existing estimators considered in the study. Keywords: Auxiliary variable; MSE; coefficient of variation; study variable; simple random sampling. Review Article