A CLASS OF RATIO-CUM-DUAL TO RATIO ESTIMATOR OF POPULATION VARIANCE
In this paper, we have proposed a class of ratio-cum-dual to ratio estimators using known values of some population parameters of the auxiliary variable to estimate the population variance of the study variable. The expressions for the bias and mean square error of the proposed estimators have been derived upto the first order of approximation. A comparison has been made with some well known estimators, such as sample variance ( 2 y s ), Isaki ratio type ( R t ) and the dual to ratio type ( t(d ) ) estimators of the population variance and it is shown that the proposed estimator is better than the mentioned estimators under the optimum condition. For illustration, an empirical study has been carried out.