本章概览 (Guide)：

• 之前我们学习了参数检验，参数检验一般用于等比/等距型数据，而且要求参数要服从正态分布和方差同质性。而对命名/顺序型数据，我们需要利用非参数检验。非参数检验虽然不如参数检验敏感，但是数据无需服从正态分布。卡方检验就是最常见的非参数检验之一。
  *Previously, we learned about parameter testing, which is generally used for proportional/isometric data and requires parameters to follow a normal distribution and homogeneity of variance. For named/sequential data, we need to use non parametric tests. Although non parametric testing is not as sensitive as parametric testing, the data does not need to follow a normal distribution. The chi square test is one of the most common non parametric tests.

学习要点 (Learning Points)：

1. 区分参数检验与非参数检验
   Distinguishing between parametric and non parametric tests
2. 了解卡方检验的基本原理
   Understand the basic principles of chi square test
3. 学习卡方分布的特点
   The characteristics of learning chi square distribution
4. 掌握卡方匹配度检验与卡方独立性检验
   Mastering the chi square matching test and chi square independence test
5. 了解卡方检验的前提与限制
   Understand the prerequisites and limitations of chi square testing
6. 学会计算卡方检验的效应量
   Learn to calculate the effect size of chi square test

目录

• 卡方检验的基本原理 (The basic principle of chi square test)
• 卡方分布 (Chi square distribution)
• 卡方匹配度检验(Chi square matching test)
• 卡方独立性检验 (Chi square independence test)
• 卡方检验的前提和限制 (The prerequisites and limitations of chi square test)
• 卡方与效应大小 (Chi square and effect size)

作业

• 2023作业 (Homework 2023)
• 2024作业 (Homework 2024)