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. It is tradition to use the auxiliary information at the estimation stage in improving the precision of the estimates of population parameters such as mean and variance. A large amount of work has been carried out towards the estimation of population mean 𝑌 ̄ of the study variable y in the presence of auxiliary information by various authors including Cochran (1940), Robson (1957), Singh, M.P. (1965, 1967), Srivastava (1971, 1980), Srivastava and Jhajj (1980), Sahai and Sahai (1985), Ray and Singh (1981), Gupta (1978), Adhvaryu and Gupta (1983), Singh and Upadhyaya (1986), Singh, H. P. (1986, 1987), Singh and Singh (1984), Tracy et al (1996), Bahl and Tuteja (1991), Singh, S. (2003), Reddy (1978), Walsh (1970), Vos (1980), Singh and Ruiz Espejo (2003), Singh
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