Generalized Family of Exponential type Estimators for the Estimation of Population Coefficient of Variation

Abstract

In this article, we proposed an improved family of estimators for population coefficient of variation (CV) under simple random sampling, which needed two helping variables. The expression for bias and mean square error (MSE) are derived up to first order of approximation, and investigated the performance of the proposed family with existing estimators in both actual and simulated conditions, found that new estimators showing lower mean square errors as compare to the existing once, it is concluded that the suggested family of estimators achieved better results.