BiasAttention & information · Availability Heuristic · Entry 14
Selection Bias – when the sample doesn’t reflect reality
Are you making conclusions based on a sample that doesn’t represent the whole picture? That’s Selection Bias – an error that occurs when data is not randomly selected and doesn’t reflect reality.
Where it can show up
- Surveys – asking only social media users excludes offline opinions.
- Medicine – testing a drug on young volunteers doesn’t reveal its effects on older patients.
- Business – successful startups seem common because failures are rarely reported.
A practical countermeasure
- Check who’s in the sample – is it truly representative?
- Look for missing groups – who was excluded from the data?
- Be cautious with generalizations – if information comes from a limited group, it may distort reality.
Keep exploring
Extension NeglectBase Rate Fallacy – when you ignore general statistics for a specific casewhen general probabilities are ignored in favor of specific cases, even when statistics provide a more accurate prediction.Read entry Extension NeglectInsensitivity to Sample Size – when small samples mislead youthe tendency to underestimate how much small samples can distort results.Read entry Availability HeuristicSurvivorship Bias – when you only see the winnersthe tendency to focus on those who ‘made it’ while ignoring those who didn’t because they’re invisible.Read entry
