An unbiased efficient estimator of population mean using an auxiliary attribute in stratified random sampling

In this present paper, an unbiased estimator of population mean is suggested by using an auxiliary attribute within stratified simple random sampling (SSRS), the variance of the estimator has been theoretically derived, considering a first-order approximation. When compared to other comparable existing estimators, the proposed one has the smallest mean square error. The simulation study is employed to the artificial generated populations to verify the theoretical findings.