On Modification of Some Estimators using Parameters of Auxiliary Information for the Estimation of the Population Coefficient of Variation

Authors

  • Awwal Adejumobi Department of Mathematics, Faculty of Physical Sciences, Kebbi State University of Science and Technology, Aliero, Nigeria https://orcid.org/0000-0003-4048-8576
  • Mojeed Abiodun Yunusa Department of Statistics, Usmanu Danfodiyo University, Sokoto, Nigeria
  • Abdulrahman Rashida State College of Basic and Remedial Studies, Sokoto, Nigeria
  • Ahmed Babatunde Issa Department of Statistics, Usmanu Danfodiyo University, Sokoto, Nigeria
  • Kabiru Abubakar Department of Mathematics and Statistics, Umaru Ali Shinkafi Polytechnic, Sokoto, Nigeria

DOI:

https://doi.org/10.56556/jtie.v3i1.729

Keywords:

Auxiliary information, Efficiency, Coefficient of Variation, Mean Square Error, Percentage Relative Efficiency

Abstract

Several studies in the theory of sampling survey have established the fact that the use of auxiliary information at the planning and estimation stages helps in enhancing the efficiency of estimators for estimating population parameters like population mean, population variance, standard deviation etc. as compared to the estimators which use not auxiliary information. In the present study, four estimators for estimating the population coefficient of variation of the study variable using auxiliary information were proposed. The properties (Biases and MSEs) of the proposed estimators were derived up to first order of approximation using Taylor series approach. Numerical analysis was conducted to justify the efficiencies of the proposed estimators and the results revealed that the proposed estimators are more efficient than the existing estimators considered in the study.

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Published

2024-02-05

How to Cite

Adejumobi, A., Mojeed Abiodun Yunusa, Abdulrahman Rashida, Ahmed Babatunde Issa, & Kabiru Abubakar. (2024). On Modification of Some Estimators using Parameters of Auxiliary Information for the Estimation of the Population Coefficient of Variation. Journal of Technology Innovations and Energy, 3(1), 12–29. https://doi.org/10.56556/jtie.v3i1.729

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Section

Research Articles