Probability

Base Rate

Also known as: Prior Probability

The unconditional prevalence of an event before any specific evidence is taken into account.

Base rate neglect - ignoring it when evidence arrives - is the most consequential reasoning error in applied probability, and interviews test it directly.

When an event is rare, the base rate dominates the posterior almost entirely. A 99%-accurate test for a 1-in-1,000 condition produces positives that are genuine less than 10% of the time, because the false positives come from a population a thousand times larger.

In trading, the same logic applies to signals: a screen that flags "unusual" activity in a market where genuine events are rare will mostly flag noise, however accurate it is in isolation.

Full guide

Bayes' Theorem for Quant Interviews

The base rate is the whole question. How to set up Bayes problems so the arithmetic is trivial, and why the famous test-accuracy trap works.

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