Efficient use of auxiliary information in estimating finite population variance in sample surveys

This is the authors' abstract. We don't add key points for this paper.

This paper addresses the problem of estimating the finite population variance of the study variable y using information on the known population variance of the auxiliary variable x in sample surveys. We have suggested a class of estimators for population variance using information on population variance of x. The bias and mean squared error of the suggested class of estimators up to first order of approximation was obtained. Preference regions were derived under which the suggested class of estimators is more efficient than the usual unbiased estimator, Das and Tripathi (1980) estimators, Isaki (1983) ratio estimator, Singh et al (1973, 1988) estimator and Gupta and Shabbir (2007) estimator. An empirical study as well as simulation study were carried out in support of the present study.