Generalized ratio-product-type estimator for variance using auxiliary information in simple random sampling

This paper suggests a new generalized ratio-product-type estimator for population variance of study variable utilizing information obtained from two auxiliary variables. Efficiency of the new estimator has been compared mathematically with the generalized ratio-product-type estimator based on information from auxiliary variable under simple random sampling without replacement. Empirically, the estimator proves more efficient than the usual unbiased estimator and some previously existing biased variance estimators under the derived conditions and for suitable choice of scalars and constants at which bias is also smaller in comparison. It is also worth-mentioning that all the estimators under discussion are the special cases of thenew generalized ratio-product-type estimator for population variance.