AI engineering glossary · Statistics inference
What is practical significance?
Practical significance: Whether an effect is large enough to matter in the real world, as opposed to merely being statistically detectable. With huge samples, trivial differences produce tiny p-values. Judging it requires business or domain context, not just a statistical calculation.
Practical significance: an example
A test on 10 million users shows p < 0.001 for a 0.01 percent lift in clicks, yet the gain may not repay the engineering cost.
Related terms
More Statistics inference terms
- Prior distribution
- Propensity score
- R-squared
- Randomisation
- Randomised controlled trial
- Regression coefficient
- Regression to the mean
- Rejection region
Where you learn it
Practical significance is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.