Improvement in variance estimation in simple random sampling

We propose a new estimator for the population variance using an auxiliary variable in simple random sampling and obtain the equations for its mean square error (MSE) and bias. In addition, theoretically, we show that the proposed estimator is more efficient than the traditional ratio and regression estimators, suggested by Isaki (1983), under certain conditions that are defined in this article. These conditions are satisfied with a numerical example.