Improved Estimation of Finite Population Variance Using Auxiliary Information.

This article addresses the problem of estimating of finite population variance using auxiliary information in simple random sampling. A ratio-cum-difference type class of estimators for population variance has been suggested with its properties under large sample approximation. It has been shown that the suggested class of estimators is more efficient than usual unbiased, difference, Das and Tripathi (1978), Isaki (1983), Singh et al. (1988), Kadilar and Cingi (2006), and other estimators/classes of estimators. In addition, we support this theoretical result with the aid of a empirical study. [ABSTRACT FROM AUTHOR]