AI engineering glossary · Statistics inference
What is potential outcomes framework?
Potential outcomes framework (also called Rubin causal model): A formal model of causality in which each unit has an outcome under each possible treatment, but only one is ever seen. Causal effects are defined as differences between these outcomes.
Potential outcomes framework: an example
For user i, Y(1) is the spend if shown the offer and Y(0) is the spend if not; only one of them is observed.
Related terms
More Statistics inference terms
- Power analysis
- Practical significance
- Prior distribution
- Propensity score
- R-squared
- Randomisation
- Randomised controlled trial
- Regression coefficient
Where you learn it
Potential outcomes framework is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.