A SUITABLE USE OF AUXILIARY INFORMATION FOR ESTIMATION OF FINITE POPULATION MEAN

Abstract

Survey statisticians are attempting to estimate the unknown population parameters efficiently. Utilizing the auxiliary information in a meaningful way allows for the efficient estimation of the finite population mean. We have proposed some modified ratio, product, and regression type estimators for the finite population mean under simple and stratified random sampling designs using transformation. To obtain even more accurate estimates, the study variable is transformed. Similar to this, a known auxiliary variable is a source for increasing the precision of estimators. In transformation, we applied the antithetic variable technique. The antithetic variable method is a variance reduction method. The method seeks to increase the precision and effectiveness of the estimators by reducing the variance of the estimates. Up to the first level of approximation, expressions for the bias and mean squared errors of the proposed estimators are obtained. The suggested estimators are compared numerically and theoretically. The performance of the suggested estimators is numerically illustrated using actual data sets to validate theoretical conclusions. The comparison showed that the proposed estimators outperformed the usual ratio, product and regression estimators