Welcome to metricsAI!
This data science platform offers a modern introduction to econometrics by combining cloud-based Python notebooks with AI learning tools from NotebookLM.
Designed as an interactive companion to Colin Cameron’s textbook, Analysis of Economics Data: An Introduction to Econometrics, metricsAI transforms static chapters into dynamic learning experiences. Students can access AI summaries, Python code, and practical examples directly in their browsers via Google Colab. There is zero setup or installation required, and the notebooks feature built-in AI tools for code generation, explanation, and transformation.
📓 Interactive Google Colab Notebooks
Click any badge below to open and run immediately in your browser:
Part I: Statistical Foundations
| Chapter | Title | Colab Notebook |
|---|---|---|
| 1 | Analysis of Economics Data |  |
| 2 | Univariate Data Summary | |
| 3 | The Sample Mean | |
| 4 | Statistical Inference for the Mean | |
Part II: Bivariate Regression
| Chapter | Title | Colab Notebook |
|---|---|---|
| 5 | Bivariate Data Summary | |
| 6 | The Least Squares Estimator | |
| 7 | Statistical Inference for Bivariate Regression | |
| 8 | Case Studies for Bivariate Regression | |
| 9 | Models with Natural Logarithms | |
Part III: Multiple Regression
| Chapter | Title | Colab Notebook |
|---|---|---|
| 10 | Data Summary for Multiple Regression | |
| 11 | Statistical Inference for Multiple Regression | |
| 12 | Further Topics in Multiple Regression | |
| 13 | Case Studies for Multiple Regression | |
Part IV: Advanced Topics
| Chapter | Title | Colab Notebook |
|---|---|---|
| 14 | Regression with Indicator Variables | |
| 15 | Regression with Transformed Variables | |
| 16 | Checking the Model and Data | |
| 17 | Panel Data, Time Series Data, Causation | |
How to Use the Notebooks
- Click any “Open in Colab” badge above
- Sign in with your Google account (free)
- Click “Run All” in the Runtime menu (or run cells individually)
- Explore and modify - change parameters, try different models, experiment with the data
- Save your work - File → Save a copy in Drive to keep your modifications
No installation, no downloads, no setup required!
👥 Authors and Credits
Carlos Mendez - Python implementation and educational notebook development
A. Colin Cameron - Original textbook, data, Stata/R code, slides.
Carlos Mendez
Associate Professor of Development Economics
My research interests focus on the integration of development economics, spatial data science, and econometrics to understand and inform the process of sustainable development across regions.