An Alternative Efficient Class of Estimators for Finite Population Mean Using Information on an Auxiliary Attribute in Sample Surveys

The crux of this article is to recast the estimator due to Koyuncu (Appl Math Comp 218:10900–10905, 2012) for the mean utilizing information on an auxiliary attribute. We have derived the bias and mean squared error of the developed estimator under large sample approximation. The best values of the constants are derived for which the mean squared error of the newly developed estimator is minimum. The region of parameters that are obtained in the envisaged estimator is more precise than Koyuncu (Appl Math Comp 218:10900–10905, 2012) estimator and other competent estimators. This reality has been also examined through an empirical study.