StatsPai - The Causal Inference Revolution: From Counterfactual Thinking to the AI Era
🚧 Content Translation in Progress
This course is currently being translated from Chinese to English.
Current Status: Translation in progress
What This Course Covers
StatsPai is a comprehensive statistics and econometrics course using Python, covering:
- Regression analysis (OLS, Logit, Probit)
- Causal inference fundamentals
- Instrumental variables (IV)
- Difference-in-Differences (DID)
- Regression Discontinuity Design (RDD)
- Panel data analysis
- Statistical visualization
- Machine learning for causal inference
- Real-world case studies
Access Chinese Version
The complete Chinese version is available now:
About This Book
Author: Bryce Wang (王几行XING) Institution: Stanford University Freeman Spogli Institute (FSI) Status: Published (Chinese), Translation in Progress (English)
Course Features
- Practical Focus: Every concept comes with Python code examples
- Real Data: Using real-world datasets from economics and social sciences
- Modern Approach: Combining traditional econometrics with machine learning
- Comprehensive: From basics to advanced causal inference methods
Stay Updated
- Watch this repository for updates: GitHub - LearnPy.online
- Follow me on Zhihu: @王几行XING
- Contact: brycew6m@gmail.com
Contribute to Translation
If you'd like to help translate this course, please:
- Fork the repository
- Create a new branch for your translations
- Submit a pull request
- Or contact me directly at brycew6m@gmail.com
We welcome all contributions!
License
This work is licensed under CC BY-NC-SA 4.0
- ✅ Attribution Required
- ❌ No Commercial Use
- ✅ ShareAlike
For commercial licensing, please contact the author.