Data Analysis Learning#
关于 CWorld 学习 Analysis Learning 一些笔记和代码。该课程使用 R 语言进行数据分析。
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点击侧栏的目录或下滑以阅览更多章节。
当然，你也可以下载 PDF 版本 的笔记。它来自 Github Actions 的自动构建，并时刻保持最新。
Development#
如果你对该项目有兴趣，请前往 Github 了解更多。
Contributions#
由于作者只是个正在浅学 Database 的初学者，所以笔记难免存在明显纰漏，还请读者们多多海涵。此外，也欢迎诸位使用 PR 或 Issues 来改善它们。
Thanks#
一些电子教材对作者学习上帮助颇多，没有这些资料，就没有这部笔记。在此对这些教材的原作者深表感谢。读者若对此项目笔记抱有疑惑，也可以仔细阅读以下教材以作弥补。
STATS201 book SWU 2023
Table of Contents#
Tutorials
Main Chapters
- 1. Getting Started with Regression
- 2. Basics of Simple Linear Regression
- 3. The null model
- 4. Fitting curves with the linear model
- 5. Linear models with a categorical (factor) explanatory variable
- 6. Multiplicative linear models
- 7. Power law linear models
- 8. Linear models with both numeric and factor explanatory variables
- 9. Linear models with both numeric and factor explanatory variables without interaction
- 10. Multiple linear regression models
- 11. Linear models with a single factor explanatory variable having three or more levels (One-way analysis of variance)
- 12. Linear models with two explanatory factor variables (Two-way analysis of variance)
- 13. Modelling count data using the Poisson distribution
- 14. Poisson modelling of count data: Two examples
- 15. Modelling proportion data using the binomial distribution
- 16. Analysis of contingency tables
About Project
License#
This project is licensed under the GPL 3.0 License.
This documention is admitted by Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
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