What is sampling bias and how do you mitigate it?
easyAnswer
- Sampling bias occurs when the sample is not representative of the target population — some groups over- or under-represented.
- Causes: convenience sampling, self-selection, survivorship bias, non-response.
- Mitigations: random sampling with a clear frame, stratified sampling to ensure coverage of subgroups, post-stratification weighting, and comparing sample demographics to population statistics.
Check yourself — multiple choice
- Convenience sampling eliminates bias
- Stratified sampling helps ensure representation of subgroups
- Survivorship bias only affects finance
- Random sampling always causes bias
Stratified sampling explicitly guarantees subgroup coverage.
#sampling#design
Practise Statistics Fundamentals
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