A New Estimator for Estimating Population Mean Using Two Auxiliary Attributes in Stratified Random Sampling

In this paper, we propose an efficient estimator for the estimation of population mean using the information of the two auxiliary attributes under stratified random sampling. The bias, mean squared error (MSE) and minimum mean squared error of the proposed estimator, up to the first order of approximation, have been derived. In theoretical comparison, the conditions have been deliberated under which the proposed estimator performs enhanced than the existing estimators. Numerical study has been demonstrated using four data sets to assess the performance as well as the applicability of all the estimators considered here.