AI engineering glossary · Probability
What is sampling bias?
Sampling bias: A systematic error caused by choosing a sample in a way that makes some members of the population more or less likely to be included than others, so results do not represent the whole. Larger samples do not fix it.
Sampling bias: an example
Surveying only people who reply to an app notification over-represents active users and misstates overall satisfaction.
Related terms
More Probability terms
- Sampling with replacement
- Sampling without replacement
- Simple random sample
- Simpson's paradox
- Skewness
- Standard deviation
- Standard normal distribution
- Stationary distribution
Where you learn it
Sampling bias is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.