Base Rate Fallacy
Ignoring how common something actually is in favor of specific but less reliable detail.
- informal
The base rate fallacy neglects the general prevalence (the base rate) of an event when judging a specific case, leaning instead on vivid individuating detail or an imperfect test. Even a highly accurate test for a rare condition yields mostly false positives, because the rarity dominates the arithmetic.
Examples
- “This test is 99% accurate and you tested positive for a disease only 1 in 10,000 people have, so you almost certainly have it.” — in fact most positives are false alarms.
- “He's quiet and loves poetry, so he's probably a literature professor rather than a delivery driver,” ignoring how many more drivers there are.
Why it works & how to counter
Persuasive because specific details feel more relevant than dry statistics. Counter it by starting from how common the thing actually is, then adjusting for the new evidence — not the other way around.