Sampling Bias Math Example 4
Follow the full solution, then compare it with the other examples linked below.
Example 4
hardAn online survey about internet usage gets 10,000 responses. Explain why this large sample does not eliminate bias, and identify what type of people are systematically excluded.
Solution
- 1 Large sample size reduces random error (noise) but cannot fix systematic bias
- 2 Online surveys only reach people who: have internet access, see the survey, and choose to respond
- 3 Excluded groups: those without internet (often elderly, low-income, rural populations), those who see but ignore the survey (non-response bias)
- 4 These excluded groups likely have very different internet usage patterns — exactly what's being measured!
Answer
Large doesn't fix bias. Excludes non-internet users and non-responders, precisely the people most relevant to the study.
This illustrates a key principle: a biased sampling method remains biased regardless of sample size. More biased data does not equal less biased conclusions. The 1936 Literary Digest poll had 2.4 million responses but predicted the wrong election winner due to sampling bias.
About Sampling Bias
Sampling bias occurs when the method of selecting a sample systematically over- or under-represents certain groups relative to their actual proportion in the population.
Learn more about Sampling Bias →More Sampling Bias Examples
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