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..
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data
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01-Introduction-To-Causality.ipynb
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02-Randomised-Experiments.ipynb
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03-Stats-Review-The-Most-Dangerous-Equation.ipynb
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04-Graphical-Causal-Models.ipynb
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05-The-Unreasonable-Effectiveness-of-Linear-Regression.ipynb
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06-Grouped-and-Dummy-Regression.ipynb
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07-Beyond-Confounders.ipynb
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08-Instrumental-Variables.ipynb
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09-Non-Compliance-and-LATE.ipynb
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10-Matching.ipynb
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11-Propensity-Score.ipynb
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12-Doubly-Robust-Estimation.ipynb
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13-Difference-in-Differences.ipynb
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14-Panel-Data-and-Fixed-Effects.ipynb
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15-Synthetic-Control.ipynb
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16-Regression-Discontinuity-Design.ipynb
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17-Predictive-Models-101.ipynb
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18-Heterogeneous-Treatment-Effects-and-Personalization.ipynb
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19-Evaluating-Causal-Models.ipynb
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20-Plug-and-Play-Estimators.ipynb
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21-Meta-Learners.ipynb
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22-Debiased-Orthogonal-Machine-Learning.ipynb
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23-Challenges-with-Effect-Heterogeneity-and-Nonlinearity.ipynb
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24-The-Diff-in-Diff-Saga.ipynb
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25-Synthetic-Diff-in-Diff.ipynb
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Conformal-Inference-for-Synthetic-Control.ipynb
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Debiasing-with-Orthogonalization.ipynb
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Debiasing-with-Propensity-Score.ipynb
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Prediction-Metrics-For-Causal-Models.ipynb
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When-Prediction-Fails.ipynb
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_config.yml
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_toc.yml
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landing-page.md
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nb18.py
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nb21.py
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sc.py
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