An Efficient Logarithmic Ratio Type Estimator of Finite Population Mean under Simple Random Sampling
Keywords:Auxiliary variable, Logarithmic ratio estimator, Bias, MSE, Efficiency
The use of auxiliary information has become indispensable for improving the exact of estimators of population parameters like the mean and variance of the variable under study. A great variety of the techniques such as the ratio, product, and regression methods of estimation are commonly known in this esteem. In this paper, we propose an efficient logarithmic ratio type estimator for finite population mean estimation under simple random sampling. The expression for the bias and mean squared error (MSE) of the proposed estimator is obtained up to the first order of approximation. The conditions under which the proposed estimator is more efficient than the existing ones are established. An empirical study using three data sets is also conducted to validate the theoretical findings and the results revealed that the suggested estimator is better than the existing estimators considered in the study.
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