本章概览 (Guide)：

• 很多情况下，变量之间虽然存在联系，却并不是因果关系。为了度量变量之间的关系，在这一章中，我们将学习相关的概念。在心理学中，相关分析可以验证变量之间的关系，还可以通过一个变量预测另一个变量的值，心理测量也离不开相关。因此，相关是很重要的概念。
  In many cases, although there is a connection between variables, it is not a causal relationship. In order to measure the relationship between variables, in this chapter, we will learn the concept of correlation. In psychology, correlation analysis can verify the relationship between variables and predict the value of another variable through one variable. Psychological measurement also relies on correlation. Therefore, correlation is a very important concept.

学习要点 (Learning points)：

1. 学习相关的定义、特点与解释
   Learning the definition, characteristics, and explanations of correlation
2. 掌握Pearson相关的应用情境和计算公式
   Master the application scenarios and calculation formulas related to Pearson correlation
3. 掌握Pearson相关的显著性检验方法
   Mastering the significance testing method of Pearson correlation
4. 掌握Spearman相关的应用情境和计算公式
   Master the application scenarios and calculation formulas related to Spearman correlation
5. 掌握Spearman相关的显著性检验方法
   Mastering the significance testing method of Spearman correlation
6. 掌握点二列相关的应用情境和计算公式
   Master the application scenarios and calculation formulas related to point biserial correlation
7. 学会利用Kendall和谐系数评定多组数据的一致性
   Learn how to use Kendall's harmony coefficient to evaluate the consistency of multiple sets of data

目录

• 相关的定义 (Related definitions)
• Pearson相关 (Pearson correlation)
• Pearson相关的统计效应与效力 (Pearson correlation's statistical effects and power)
• Pearson相关的显著性检验 (Significance test of Pearson correlation)
• Spearman相关 (Spearman correlation)
• 点二列相关 (Point biserial correlation)
• Kendall和谐系数 (Kendall's harmony coefficient)

作业

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