The present article addresses the effects of measurement errors on the estimation of population coefficient of variation C Y of the study variable Y. Bias and mean squared error (MSE) of the proposed estimator are derived upto the first order of approximation under simple random sampling design. A theoretical efficiency comparison is made between the proposed estimator and the usual coefficient of variation estimator in presence of measurement errors. Based on large sample approximations the optimal condition is obtained under which the proposed estimator performs better than the conventional estimator in presence of measurement errors. Theoretical results are verified by the simulation study using R software.
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