This repository is notes from the Udacity Course Causal Inference, conducted by Jonathan Hershaff. The original notebooks from this class is also available here on github.
- Correlation vs Causation
- Two Languages of Causality: DAG and Potential Outcomes Framework
- Interrupted Time Series
- Interrupted Time Series Exercise
- Difference in Differences (DiD)
- DiD exercise
- Pre-event validation and testing
- Test DiD assumptions
- Placebo Test
- Placebo test with DiD
- Event Studies
- Event Studies Exercise
- Modeling Time Varying Effects
- EVent Study Model Validation
- Event Study Lead Lag Coefficients Exercise
- Event Study with Staggered Rollout
- Staggered Rollout (Dividents example) Exercise
- Synthetic Control with Lasso
- Synthetic Control Exercise
- Model Validation with Simulated Data
- Compare Models
- Bayesian Structural Time Series Causallimpact in R
- Regression Discontinuity
- Regression Discontinuity Exercise
- Regression Discontinuity Model Validation and Sensitivity of Bandwidth
- Regression Discontinuity Model Validation Exercise
- Communicating Non-Experimental Causal Results
- Presenting Results to Stakeholders Example
- Final Project