Improved Ratio Type Estimators Using Auxiliary Attribute for Population Variance

This paper proposes a family of estimators based on the auxiliary information on a attribute. The bias and mean squared error are obtained up to the first order of approximation. The theoretical comparison are also supported by numerical examples based on the two natural populations, showing the superiority of the suggested family of estimators, both theoretically as well as empirically over estimators available in literature.