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What is a Base Rate Fallacy?

 , updated on February 04, 2018
The base rate fallacy is a tendency to focus on specific information over general probabilities. For example:
1 in 1000 students cheat on an exam
A cheating detection system catches cheaters with a 5% false positive rate
All 1000 students are tested by the system
The cheating detection system catches Sara
What is the chance that Sara is innocent?
Many people who answer the question focus on the 5% false positive rate and exclude the general statistic that 999 out of 1000 students are innocent. This results in the incorrect answer that there is a 5% chance that Sara is innocent. This incorrect answer neglects the fact that by testing 1000 students, the machine will catch 50 students on average and 49 of these students will be innocent. Therefore, there is approximately a 98% chance that Sara is innocent.
Overview: Base Rate Fallacy
Type
Definition
Focusing on a specific probability while ignoring a more general probability.
Related Concepts

Cognitive Biases

This is the complete list of articles we have written about cognitive biases.
Ambiguity Effect
Anchoring
Backfire Effect
Base Rate
Biased
Biases
Circular Reasoning
Cognitive Bias
Cognitive Dissonance
Complexity Bias
Crab Mentality
Creeping Normality
Curse Of Knowledge
Decoy Effect
Ethnocentrism
Exposure Effect
False Analogy
False Hope
Fear Of Youth
Gambler's Fallacy
Golden Hammer
Halo Effect
Hindsight Bias
Negativity Bias
Optimism Bias
Peak-End Rule
Positive Bias
Sour Grapes
Survivorship Bias
Us vs Them
Victim Mentality
Wishful Thinking
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