本章概览 (Guide)：

• 在上一章，我们重点介绍了非参数检验最常见的一种方法：卡方检验。在这一章中，我们将介绍另外几种非参数检验方法。这些方法也不依赖于特定的总体分布，无须对总体参数规定条件。
  In the previous chapter, we focused on the most common method of non parametric testing: chi square test. In this chapter, we will introduce several other non parametric testing methods. These methods also do not rely on specific population distributions and do not require specifying conditions for population parameters.
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学习要点 (Learning Points)：

1. 了解非参数检验的使用情景与优缺点
   Understand the usage scenarios and advantages and disadvantages of non parametric testing
2. 学会用秩统计量将顺序型数据重新排列
   Learn to use rank statistics to rearrange sequential data
3. 学会利用其他5种非参数检验方法进行假设检验
   Learn to use 5 other non parametric testing methods for hypothesis testing
4. 掌握这些非参数检验方法在大样本下的近似
   Master the approximation of these non parametric testing methods in large samples
5. 掌握这些非参数检验方法的统计前提
   The statistical prerequisites for mastering these non parametric testing methods
6. 了解置换检验的原理
   Understand the principles of permutation testing

目录

• 顺序型数据和秩统计量 (Sequential data and rank statistics)] * [[曼-惠特尼U检验|曼-惠特尼U检验 (Mann Whitney U-test)
• 符号检验法 (Symbol testing method)
• 维尔克松T检验 (Wilcoxon T-test)
• 克-瓦氏单向方差分析 (K-W one-way analysis of variance)
• 费里德曼双向方差分析 (Friedman's two-way analysis of variance)
• 置换检验 (Permutation test)

作业

• 2023作业 (Homework2023)
• 2024作业 (Homework2024)