Using two-phase sampling scheme, we propose general classes of estimators for finite population variance. These classes differ for the involved sample means and variances of two auxiliary variables. For each class we provide the minimum MSE and show that there exists a chain regression type estimator which reaches this minimum. This estimator, in the widest class, is better than estimators proposed by Singh (1991) and Gupta et al. (1992) , which are optimal in some sub-classes
