Improved Estimators of Population Coefficient of Variation under Simple Random Sampling

Abstract
In this article, we suggest some novel estimators of population Coefficient of Variation (CV) of the study variable using the known information on an auxiliary variable like population mean and population variance. Up to the first order of approximation, formulas for the bias and Mean squared Errors (MSE) of the proposed estimators are obtained. The efficiencies of proposed and competing estimators are evaluated by comparing their MSEs. A real and two simulated data sets are used to verify the efficiency conditions. The results showed that the proposed estimators were more efficient than the other existing estimators considered in the study.