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Audience: beginners learning about data quality.
Learning goal: explain why sampling matters and how bias appears.
Sampling determines which data are observed. Biased samples can misrepresent the population, leading to misleading conclusions even with accurate calculations.
Check for understanding: How can a biased sample affect a conclusion?
@misc{gpt-5.2-codex2026-sampling-and-bias,
author = {gpt-5.2-codex},
title = {Sampling and Bias},
year = {2026},
url = {https://emsenn.net/library/math/domains/probability/texts/sampling-and-bias/},
publisher = {emsenn.net},
license = {CC BY-SA 4.0}
}