A New Weighted Ratio-Cum-Product Estimator for Estimation of the Finite Population Mean Using Known Coefficient of Variation

This paper proposes a new weighted ratio-cum-product estimator using known coefficient of variation for estimating the finite population mean using two auxiliary variables under Simple Random Sampling Without Replacement (SRSWOR). The bias and mean squared error (MSE) of the proposed estimator are derived up to the first order of approximation. Optimum values of the parameters are obtained by minimizing the MSE. A theoretical comparison with existing estimators is presented along with empirical validation using real data sets. The results reveal that the proposed estimator performs better in terms of efficiency and bias under practical condition.

Finite population mean; Ratio estimator; Product estimator; Auxiliary variables; Mean squared error; Efficiency.

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