Base Rate Neglect

The tendency to ignore or underweight the base rate (overall frequency) of an event when evaluating specific cases—focusing instead on vivid, case-specific information. A test that's 99% accurate for a disease that affects 1 in 10,000 people will produce mostly false positives—but people hearing '99% accurate' assume a positive test means they're 99% likely to have the disease. The error: ignoring that the base rate (1/10,000) overwhelms the test accuracy. Base rate neglect explains overreaction to rare dramatic events, overestimation of startup success rates by founders, and misinterpretation of diagnostic tests.

When to use it

When evaluating specific cases and tempted to ignore category-level statistics; when diagnostic tests produce results that feel certain but depend on base rates; when confidence about a specific outcome exceeds what base rates warrant; when designing evaluation processes that need to integrate case-specific and category-level information.

How it can help

For any specific-case judgment, FIRST check the base rate. 'This candidate seems exceptional' → what percentage of candidates who seem exceptional actually perform exceptionally? 'This startup will succeed' → what's the base rate of startup success in this category? 'This investment will outperform' → what percentage of investments in this class outperform? The base rate is your prior; specific evidence updates it but rarely overrides it. Use Bayes' theorem intuitively: specific evidence should SHIFT your estimate from the base rate, not REPLACE it.