1.1 本指南涵盖并简要介绍了一些普遍接受的统计分析方法，这些方法有助于解释腐蚀试验结果。 1.2 本指南不包括详细的计算和方法，而是涵盖了在腐蚀测试中应用的一系列方法。 1.3 本指南仅考虑了在腐蚀试验中被广泛接受的统计方法。 1.4 以国际单位制表示的数值应视为标准。本标准不包括其他计量单位。 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====== 3.1 由于多种因素，腐蚀试验结果往往比许多其他类型的试验更为分散，包括微小杂质通常在控制腐蚀速率方面起决定性作用。统计分析非常有助于研究人员解释这些结果，尤其是在确定测试结果何时存在显著差异时。当测试各种材料时，这可能是一项困难的任务，但统计方法为解决这个问题提供了一种合理的方法。 3.2 现代数据简化程序与计算机相结合，相对容易地对数据集进行复杂的统计分析。这种能力使研究人员能够确定许多变量之间是否存在关联，如果存在，则可以开发与变量相关的定量表达式。 3.3 统计评估是分析任何提供定量信息的程序的结果的必要步骤。该分析允许根据测量结果来估计置信区间。

1.1 This guide covers and presents briefly some generally accepted methods of statistical analyses which are useful in the interpretation of corrosion test results. 1.2 This guide does not cover detailed calculations and methods, but rather covers a range of approaches which have found application in corrosion testing. 1.3 Only those statistical methods that have found wide acceptance in corrosion testing have been considered in this guide. 1.4 The values stated in SI units are to be regarded as standard. No other units of measurement are included in this standard. 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 ====== 3.1 Corrosion test results often show more scatter than many other types of tests because of a variety of factors, including the fact that minor impurities often play a decisive role in controlling corrosion rates. Statistical analysis can be very helpful in allowing investigators to interpret such results, especially in determining when test results differ from one another significantly. This can be a difficult task when a variety of materials are under test, but statistical methods provide a rational approach to this problem. 3.2 Modern data reduction programs in combination with computers have allowed sophisticated statistical analyses on data sets with relative ease. This capability permits investigators to determine if associations exist between many variables and, if so, to develop quantitative expressions relating the variables. 3.3 Statistical evaluation is a necessary step in the analysis of results from any procedure which provides quantitative information. This analysis allows confidence intervals to be estimated from the measured results.