On Improved Estimation of Population Mean Using Known Coefficient of Skewness of an Auxiliary Variable

This paper proposes an improved general family of ratio-type estimators using the coefficient of skewness of an auxiliary variable for estimating finite population mean under simple random sampling. Bias, mean squared error (MSE) and minimum MSE of the proposed family are derived up to the first degree of approximation. It is found that proposed family behaves better than competing estimators under some simple conditions. Theoretical findings are confirmed with numerical illustration using three natural populations. In addition, Monte Carlo simulation study on a real data set also proves the potential of the proposed family against the common unbiased estimator, traditional ratio estimator and estimators by Yan and Tian (CCIS 106:103–110, 2010).