Improved Ratio-Cum-Product Estimators of Population Mean Using Known Population Parameters of Auxiliary Variables

In the present paper, a ratio-cum-product type estimator of finite population mean using known coefficient of kurtosis and median of auxiliary variable has been proposed. The explicit expressions for bias and mean squared error of the proposed estimator with large sample approximation are derived up to the first order of approximation. A comparison has been made with the existing estimators of population mean using auxiliary variable under simple random sampling scheme. An empirical study is also carried out to demonstrate the performance of the suggested estimator along with the existing estimators of population mean under simple random sampling. It has been shown through the empirical study that the proposed estimator has minimum mean squared error among all existing estimators of population mean. It is the best estimator of population mean among all existing estimators.