1.1 本指南定义了离散总体、面积和散装材料概率采样的术语并介绍了基本方法。它概述了ASTM标准用户使用的常见概率抽样方法。 1.2 采样可以是为了估计、在采样群体的各部分之间进行比较或接受批次。抽样还用于审计从人口的完整列举中获得的信息。 1.3 本标准中未规定单位制。 1.4 本标准并非旨在解决与其使用相关的所有安全问题（如有）。本标准的使用者有责任在使用前制定适当的安全、健康和环境实践，并确定监管限制的适用性。 1.5 本国际标准是根据世界贸易组织技术性贸易壁垒委员会发布的《关于制定国际标准、指南和建议的原则的决定》中确立的国际公认的标准化原则制定的。 ===意义和用途====== 4.1 本指南介绍了抽样设计的主要类型，并提供了估计总体平均数和估计标准误差的公式。实践 E105 提供了根据研究目标、成本和实际约束设计概率抽样计划的原则。实践 E122 有助于指定所需的样本量。实践 E141 描述了确保采样结果有效性的条件。 对本指南中的设计和公式的进一步描述，以及除此之外的内容，可以在教科书中找到 ( 1- 10 ) 。 3. 4.2 采样，包括离散采样和批量采样，是一项文书和实物操作。它通常包括培训普查员和技术人员使用地图、目录和秒表，以定位指定的采样单位。一旦采样单元位于其地址，离散采样和区域采样枚举将进行测量。对于批量采样，将材料提取成复合材料。 4.3 采样计划由说明如何列出地址以及如何选择要测量或提取的地址组成。帧是一个地址列表，每个地址都由一个整数或一个n元组（几个整数）索引。采样总体由帧中可以实际选择和测量的所有地址组成。 它有时与用户希望覆盖的目标人群不同。 4.4 选择方案指定哪些索引构成样本。如果认证随机数完全控制了选择方案，则样本称为概率样本。认证随机数是从表中生成的随机数（例如，Ref ( 11 ) )它已经过等数字频率和串行独立性的测试，来自被检查为具有长周期长度的计算机程序，或者来自随机物理方法，如投掷硬币或赌场质量的旋转器。 4.5 抽样的目的通常是通过相应的样本平均值来估计某个感兴趣变量的总体平均值。通过采用概率抽样，可以从根本上消除选择偏差，因此离散抽样中样本设计的主要目标是减少抽样方差。

1.1 This guide defines terms and introduces basic methods for probability sampling of discrete populations, areas, and bulk materials. It provides an overview of common probability sampling methods employed by users of ASTM standards. 1.2 Sampling may be done for the purpose of estimation, of comparison between parts of a sampled population, or for acceptance of lots. Sampling is also used for the purpose of auditing information obtained from complete enumeration of the population. 1.3 No system of units is specified in this standard. 1.4 This standard does not purport to address all of the safety concerns, if any, associated with its use. It is the responsibility of the user of this standard to establish appropriate safety, health, and environmental practices and determine the applicability of regulatory limitations prior to use. 1.5 This international standard was developed in accordance with internationally recognized principles on standardization established in the Decision on Principles for the Development of International Standards, Guides and Recommendations issued by the World Trade Organization Technical Barriers to Trade (TBT) Committee. ====== Significance And Use ====== 4.1 This guide describes the principal types of sampling designs and provides formulas for estimating population means and standard errors of the estimates. Practice E105 provides principles for designing probability sampling plans in relation to the objectives of study, costs, and practical constraints. Practice E122 aids in specifying the required sample size. Practice E141 describes conditions to ensure validity of the results of sampling. Further description of the designs and formulas in this guide, and beyond it, can be found in textbooks ( 1- 10 ) . 3 4.2 Sampling, both discrete and bulk, is a clerical and physical operation. It generally involves training enumerators and technicians to use maps, directories and stop watches so as to locate designated sampling units. Once a sampling unit is located at its address, discrete sampling and area sampling enumeration proceeds to a measurement. For bulk sampling, material is extracted into a composite. 4.3 A sampling plan consists of instructions telling how to list addresses and how to select the addresses to be measured or extracted. A frame is a listing of addresses each of which is indexed by a single integer or by an n-tuple (several integer) number. The sampled population consists of all addresses in the frame that can actually be selected and measured. It is sometimes different from a targeted population that the user would have preferred to be covered. 4.4 A selection scheme designates which indexes constitute the sample. If certified random numbers completely control the selection scheme the sample is called a probability sample. Certified random numbers are those generated either from a table (for example, Ref ( 11 ) ) that has been tested for equal digit frequencies and for serial independence, from a computer program that was checked to have a long cycle length, or from a random physical method such as tossing of a coin or a casino-quality spinner. 4.5 The objective of sampling is often to estimate the mean of the population for some variable of interest by the corresponding sample mean. By adopting probability sampling, selection bias can be essentially eliminated, so the primary goal of sample design in discrete sampling becomes reducing sampling variance.