AI engineering glossary · Statistics inference
What is difference-in-differences?
Difference-in-differences (also called DiD): A method that compares the change over time in a treated group with the change over the same period in an untreated group. It removes stable group differences and shared trends, under the assumption of parallel trends.
Difference-in-differences: an example
Sales in cities where a new delivery service launched rose by 12 percent while other cities rose by 5 percent, giving an estimated effect of 7 points.
Related terms
More Statistics inference terms
- Effect size
- Efficiency
- Estimator
- F-test
- False discovery rate
- Family-wise error rate
- Fisher information
- Fisher's exact test
Where you learn it
Difference-in-differences is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.