1.1本指南涵盖了分析风化实验常见数据的基本统计方法。这些方法用于决策，其中的实验旨在测试单个响应变量的假设。该方法适用于自然或实验室风化。 1.2仅介绍了基本统计方法。有许多其他方法可能适用于也可能不适用于本指南未涵盖的风化试验。 1.3本指南并非统计手册，因此需要一些基本和中间统计的一般知识。本指南末尾引用的教科书对基础培训很有用。 1.4本指南未对材料进行严格处理。它旨在成为实用统计方法应用于耐久性和风化领域中出现的实际问题的参考工具。重点是结果的解释。 许多书都是关于介绍性统计概念、统计公式和表格的。读者可参考这些文件以获取更详细的信息。包括各种方法的示例。示例显示了用于说明目的的典型风化数据，并不代表特定材料或暴露。 ====意义和用途====== 4.1作为风化程序的一部分，正确使用统计数据可以大大提高结果的有用性。研究风化性能数据需要基本了解统计学。适当的实验设计和统计分析大大提高了决策能力。在风化过程中，暴露可变性、方法精度和偏差、测量误差和材料可变性带来了许多不确定性。统计分析用于帮助确定哪些产品更好，哪些测试方法最适合衡量最终使用性能，以及结果的可靠性。 4.2风化暴露的结果可以显示产品之间或重复测试之间的差异。这些结果可能显示出统计上不显著的差异。正确使用风化数据的统计数据可以提高得出有效结论的概率。

1.1 This guide covers elementary statistical methods for the analysis of data common to weathering experiments. The methods are for decision making, in which the experiments are designed to test a hypothesis on a single response variable. The methods work for either natural or laboratory weathering. 1.2 Only basic statistical methods are presented. There are many additional methods which may or may not be applicable to weathering tests that are not covered in this guide. 1.3 This guide is not intended to be a manual on statistics, and therefore some general knowledge of basic and intermediate statistics is necessary. The text books referenced at the end of this guide are useful for basic training. 1.4 This guide does not provide a rigorous treatment of the material. It is intended to be a reference tool for the application of practical statistical methods to real-world problems that arise in the field of durability and weathering. The focus is on the interpretation of results. Many books have been written on introductory statistical concepts and statistical formulas and tables. The reader is referred to these for more detailed information. Examples of the various methods are included. The examples show typical weathering data for illustrative purposes, and are not intended to be representative of specific materials or exposures. ====== Significance And Use ====== 4.1 The correct use of statistics as part of a weathering program can greatly increase the usefulness of results. A basic understanding of statistics is required for the study of weathering performance data. Proper experimental design and statistical analysis strongly enhances decision-making ability. In weathering, there are many uncertainties brought about by exposure variability, method precision and bias, measurement error, and material variability. Statistical analysis is used to help decide which products are better, which test methods are most appropriate to gauge end use performance, and how reliable the results are. 4.2 Results from weathering exposures can show differences between products or between repeated testing. These results may show differences which are not statistically significant. The correct use of statistics on weathering data can increase the probability that valid conclusions are derived.