midStatistics
What is sampling bias and how does it affect statistical inference?
Updated May 17, 2026
Short answer
Sampling bias occurs when a sample is not representative of the population.
Deep explanation
Sampling bias introduces systematic error in estimation because certain groups are overrepresented or underrepresented. This violates randomness assumptions and leads to biased estimators, affecting confidence intervals, hypothesis tests, and predictive modeling.
Real-world example
Online surveys only collecting responses from internet users exclude offline populations, skewing results.
Common mistakes
- Assuming large sample size automatically removes bias.
Follow-up questions
- What is selection bias?
- How do you reduce sampling bias?