Quartile Double Ranked Set Sampling (QDRSS) is investigated for estimating the population mean. The QDRSS estimators are compared to the simple random sampling (SRS), ranked set sampling (RSS) and quartile ranked set sampling (QRSS) estimators. It is shown that, the QDRSS estimators are unbiased for the population mean when the underlying distribution is symmetric, and have small biases when the underlying distribution is asymmetric. It turns out that the QDRSS is superior to the SRS, RSS and QRSS based on the same number of measured units. A real data set of "trees' olive yields" is used to illustrate the method. X 1(1:m) , X 2(2:m) , . . . , X m(m:m)(1)Assume that the variable of interest X has a density function f X and a distribution function F X with mean µ, and variance σ 2 . Let f (i:m) denote the density function of the ith, i = 1, . . . , m, order statistic denoted X (i:m) of a random sample of size m. Then, f (i:m) is given by:The mean and the variance of X (i:m) are given by:Brought to you by |