Improvement in Estimating the Population Mean in Simple Random Sampling Using Information on Two Auxiliary Attributes and Numerical Application in Agricultural Engineering

Abstract

This study proposes a family of estimators for calculating population mean using auxiliary attributes based on an adaption of the estimators presented by Abu-Dayyeh et al. [1]. Theoretically, we obtain the mean square error (MSE) for these two classes of estimators. We considered some special cases of these estimators and compared with MSE values of proposed estimators. As a result of these comparisons, we observed that our proposed estimators give more efficient results than all other estimators in terms of MSE. In addition, we demonstrated how to extend the family of estimators when information on more than two auxiliary attributes are available. We used two numerical applications in agricultural engineering to support these theoretical results. Therefore, the suggested estimator could be applied across a broad spectrum of sampling survey.