Last update: November 21, 2024
When you get the chance to teach someone in the future, it’s a good strategy to think about entertaining yourself first—as I do—before trying to please your students. That’s how the academic baton is passed to the next generation, and no matter what happens in the world, this is what education is really about. (T. Adachi, July 2020)
Information is available at PandA.
Textbook: Gábor Békés and Gábor Kézdi, Data Analysis for Business, Economics, and Policy (Cambridge University Press, 2021)
Companion website: Gabors Data Analysis
Note that the participating students are assumed to have basic knowledge of statistics (such as mean, variance, correlation, joint distribution, hypothesis testing, etc.).
1. Regression (1): Single-Variable Regression
2. Regression (2): Multiple-Variable Linear Regression
3. Regression (3): Modeling Probabilities: The Case of Limited Dependent Variable
4. Regression (4): Demand Estimation: Introducing Endogeneity
5. Panel Data (1): Fixed-Effects and First-Difference Estimation
6. Panel Data (2): Choosing Appropriate Control Groups for Panel Data (Synthetic Control; Event Study)
7. Panel Data (3): Difference-in-Differences
8. Other Parsimonious Methods for Observational Data: Propensity Score Matching; Regression Discontinuity Design
9. Prediction (1): Regression with Time Series Data
10. Prediction (2): Forecasting
11. Prediction (3): A Framework for Prediction
12. Prediction (4): Model Building for Prediction
13. Prediction (5): Regression Trees
14. Prediction (6): Random Forrest and Boosting
15. Prediction (7): Probability Prediction and Classification
Information is available at PandA.
Textbook: Gábor Békés and Gábor Kézdi, Data Analysis for Business, Economics, and Policy (Cambridge University Press, 2021)
Companion website: Gabors Data Analysis
Information is available at PandA.
Textbook: Gábor Békés and Gábor Kézdi, Data Analysis for Business, Economics, and Policy (Cambridge University Press, 2021)
Companion website: Gabors Data Analysis
Textbook: Gábor Békés and Gábor Kézdi, Data Analysis for Business, Economics, and Policy (Cambridge University Press, 2021)
Companion website: Gabors Data Analysis
Introduction to R (by courtesy of Professor Toyoma; from his course webpage)
(2) Comparison and Correlation (all subsequent files will be uploaded at PandA)
(3) Generalizing from Data
(4) Testing Hypotheses
(5) Simple Regression
(6) Generalizing Results of a Regression
(7) Multiple Linear Regression
(8) Modeling Probabilities
(9) Regression with Time Series Data
(10) Forecasting from Time Series Data
(11) A Framework for Causal Analysis
(12) Difference-in-Differences
(13) Methods for Panel Data
(14) Appropriate Control Groups for Panel Data
(Withered Tree at Kiyomizu Temple, Kyoto)
(A lane in the Gion Area, Kyoto)