AI engineering glossary · Statistics inference
What is causal inference?
Causal inference: The set of methods for working out whether and how much one factor changes another, rather than merely moving with it. It combines study design, assumptions and statistical adjustment. It matters in AI work whenever you must decide what to change, not just predict what will happen.
Causal inference: an example
Estimating how much a loyalty programme raises repeat purchases, after accounting for the fact that keen shoppers join it.
Related terms
More Statistics inference terms
- Chi-square goodness-of-fit test
- Chi-square test of independence
- Cohen's d
- Confidence interval
- Confidence level
- Consistency
- Contingency table
- Control group
Where you learn it
Causal inference is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.