本章概览 (Guide)：

• t-检验和 z-检验不能用于多于2组的数据. 处理这类数据需要用 一种新的推论统计程序: 方差分析（ANOVA）。在方差分析中，我们利用F统计量来比较多组数据之间是否有显著差异。在统计显著性的基础上，我们又会应用两种事后检验方法比较两两之间的差异性，并对ANOVA的效应进行评估。
  T-test and Z-test cannot be used for data with more than 2 groups Processing such data requires a new inferential statistical program: Analysis of Variance (ANOVA). In analysis of variance, we use the F-statistic to compare whether there are significant differences between multiple sets of data. On the basis of statistical significance, we will apply two post hoc test methods to compare the differences between the two pairs and evaluate the effect of ANOVA.

学习要点 (Learning Points)：

1. 区分单因素设计与因素设计
   Distinguish single factor design and factor design
2. 掌握ANOVA的逻辑
   Master the logic of ANOVA
3. 理解方差的可分解性
   Understand the decomposability of variance
4. 学会计算F统计值
   Learn how to calculate F-value
5. 掌握利用简便公式进行ANOVA的方法
   Master the method of using simple formulas for ANOVA
6. 学会进行事后检验
   Learn to conduct post hoc testing
7. 学会计算ANOVA的效应
   Learn to calculate the power of ANOVA

目录

• 单因素设计 (Single factor design)
• 方差的分解 (Decomposition of variance)
• F统计值 (F-value)
• ANOVA的步骤 (Steps of ANOVA)
• 事后检验(Hoc testing)
• ANOVA的效应 (Power of ANOVA)

作业

• 2023作业 (homework of 2023)
• 2024作业 (homework of 2024)