Improvement in estimating the population mean using two-stage balanced groups ranked set sampling

Abstract

The problem of estimating the population mean using two-stage balanced groups ranked set sampling (TSBGRSS) is considered. The TSBGRSS estimator is compared with other mean estimators using simple random sampling (SRS), ranked set sampling (RSS), extreme ranked set sampling (ERSS), median ranked set sampling MRSS), and balanced groups ranked set sampling (BGRSS) estimators. For symmetric distributions considered in this study, the TSBGRSS estimator is an unbiased and more efficient than the SRS, RSS, ERSS, MRSS, and BGRSS. Estimation in the case of asymmetric distributions is addressed.