Abstract: Stratified double extreme ranked set sampling
(SDERSS) method is introduced and considered for estimating the
population mean. The SDERSS is compared with the simple random
sampling (SRS), stratified ranked set sampling (SRSS) and stratified
simple set sampling (SSRS). It is shown that the SDERSS estimator
is an unbiased of the population mean and more efficient than the
estimators using SRS, SRSS and SSRS when the underlying
distribution of the variable of interest is symmetric or asymmetric.
Abstract: In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.