A brief guide to sampling in educational settings

IF 1.3
A. George
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Abstract

This tutorial gives an overview of sampling techniques commonly used in the field of education such as simple randomized sampling, stratification methods and (multistage) cluster randomized sampling. Advantages and disadvantages of these techniques are describedwithout diving too deep into sampling theory. Instead, each technique is exemplified with data and program code in R. Finally, all presented techniques are combined to show the complexity of samples in famous educational large-scale studies such as PISA. Again an example with R code illustrates the theoretical descriptions.
教育环境中抽样的简要指南
本教程概述了教育领域常用的抽样技术,如简单随机抽样、分层方法和(多阶段)集群随机抽样。这些技术的优点和缺点的描述没有深入到抽样理论。相反,每种技术都用r中的数据和程序代码来举例说明。最后,将所有提出的技术结合起来,以显示著名的教育大规模研究(如PISA)中样本的复杂性。同样,用R代码的例子说明了理论描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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