PREDICTIVE ESTIMATION OF FINITE POPULATION MEAN USING COEFFICIENT OF KURTOSIS AND MEDIAN OF AN AUXILIARY VARIABLE UNDER SIMPLE RANDOM SAMPLING SCHEME

T he present article deals with the predictive estimation of finite population mean using coefficient of kurtosis and median of the auxiliary variable under simple random sampling scheme. Motivated by Milton et al. [2017], we have proposed an improved ratio type predictive estimator of finite population mean. Bias and mean squared error (MSE) of the proposed estimator are also obtained up to first order of approximation. Theoretical efficiency comparison of proposed estimator with Bahl and Tuteja [1991] estimator and Singh et al. estimator [2014] has also been carried out. Optimum conditions, under which the proposed estimator performs better than the competing estimators are also derived. To amply corroborate the theoretical findings, an empirical study has also been carried out. The percent relative efficiencies of the proposed estimator over existing estimators have also been obtained. The suitability of the proposed estimator can be established and appreciated as it has lesser mean squared error, when compared to other widely used estimators.