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Estimation of population mean and variance in flock management: a ranked set sampling approach in a finite population setting

机译:种群管理中种群均值和方差的估计:有限种群环境中的排序集抽样方法

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Ranked set sampling is a sampling technique that provides substantial cost efficiency in experiments where a quick, inexpensive ranking procedure is available to rank the units prior to formal, expensive and precise measurements. Although the theoretical properties and relative efficiencies of this approach with respect to simple random sampling have been extensively studied in the literature for the infinite population setting, the use of ranked set sampling methods has not yet been explored widely for finite populations. The purpose of this study is to use sheep population data from the Research Farm at Ataturk University, Erzurum, Turkey, to demonstrate the practical benefits of ranked set sampling procedures relative to the more commonly used simple random sampling estimation of the population mean and variance in a finite population. It is shown that the ranked set sample mean remains unbiased for the population mean as is the case for the infinite population, but the variance estimators are unbiased only with use of the finite population correction factor. Both mean and variance estimators provide substantial improvement over their simple random sample counterparts.
机译:等级集抽样是一种抽样技术,可在实验中提供大量成本效益,在这种情况下,可以使用快速,廉价的排名程序对单位进行正式,昂贵和精确的测量。尽管在文献中已经针对无限人口设置对这种方法相对于简单随机抽样的理论性质和相对效率进行了广泛研究,但是对于有限人口,尚未广泛探索使用排序集抽样方法。这项研究的目的是利用土耳其埃尔祖鲁姆市阿塔图尔克大学研究农场的绵羊种群数据,证明排名集抽样程序相对于更普遍使用的简单随机抽样估计种群均值和方差的实际好处。有限的人口。结果表明,与无穷人口一样,排名集样本均值对于总体均值仍然保持不变,但是仅使用有限总体校正因子才能使方差估计量保持不变。均值和方差估计量均比其简单的随机样本对应物有了实质性的改进。

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