<p>For understanding any phenomena, whether in a real or practical situation, one needs to know about the variability in the characteristics under study. Information about the variability in past and current situations is important. Therefore, the Exponentially Weighted Moving Average (EWMA) statistic is used to estimate the population variance with auxiliary information. For the purpose of estimating population variance, we have designed a memory-type class of estimator. The expressions for mean squared error (MSE) of the proposed class of estimators are derived up to the first order of approximation. A comprehensive simulation study is presented to evaluate the performance of the proposed estimator and to compare the proposed estimator with the existing memory-type estimator. The results of the simulation study are supported by an empirical investigation that is provided using data from real-world sources.</p>