An Efficient Class of Estimators for the Population Mean Using Auxiliary Information in Stratified Random Sampling

Abstract

This article addresses the problem of estimating the population mean in stratified random sampling using the information of an auxiliary variable. A class of estimators for population mean is defined with its properties under large sample approximation. In particular, various classes of estimators are identified as particular member of the suggested class. It has been shown that the proposed class of estimators is better than usual unbiased estimator, usual combined ratio estimator, usual product estimator, usual regression estimator and Koyuncu and Kadilar (2009) class of estimators. The results have been illustrated through an empirical study.

Keywords:

• Auxiliary variable
• Study variable
• Bias
• Mean square error
• Stratified random sampling

Mathematics Subject Clasififacion:

• 62D05