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An improved exponential estimator of finite population mean in simple random sampling using an auxiliary attribute
Authors:Lovleen Kumar Grover  Parmdeep Kaur
Institution:Department of Mathematics, Guru Nanak Dev University, Punjab, India
Abstract:In this paper, we propose an exponential ratio type estimator of the finite population mean when auxiliary information is qualitative in nature. Under simple random sampling without replacement scheme, the expressions for the bias and the mean square error of the proposed estimator have been obtained, up to first order of approximation. To show that our proposed estimator is more efficient as compared to the existing estimators, we have made a comparative study with respect to their mean square errors. Theoretically and numerically, we have found that our proposed estimator is always more efficient as compared to its competitor estimators including all the estimators of Abd-Elfattah et al. 1] A.M. Abd-Elfattah, E.A. El-Sherpieny, S.M. Mohamed, and O.F. Abdou. Improvement in estimating the population mean in simple random sampling using information on auxiliary attribute. Applied Mathematics and Computation, 215 (2010), 4198-4202].
Keywords:Auxiliary attribute  Bias  Mean square error  Percent relative efficiency  Point bi-serial correlation  Simple random sampling  Study variable
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