In this video, I introduce the most important assumptions in casual inference that we use in order to avoid mistakes such as presuming association and causation to be one and the same, among others:
- Positivity
- SUTVA
- Large Sample Size
- Double Blinded
- No Measurement Error
- Exchangeability
Enjoy!
