Law of Small Numbers
Version 1.0.0 · Updated 2026-07-30
CORE DEFINITION
Proposed by Tversky and Kahneman (as opposed to the Law of Large Numbers). It refers to people's erroneous belief that small samples can accurately reflect the characteristics of the population. For example: if you flip a coin three times and get heads each time, you might think the coin is biased (but this is highly likely in small samples).
SCAFFOLDING EFFECT
Reduce cognitive load
- Demystification: When you see "a fund manager has beaten the market for three consecutive years," don't rush to admire. Among thousands of managers, the number who achieve this by pure luck (Law of Small Numbers) is far larger than you think.
Anchor fast decisions
Contrasted with the Law of Large Numbers, it refers to people's erroneous belief that small samples can reliably reflect the population just like large samples, leading to overconfident conclusions drawn from few observations.
MINIMUM ACTION
In progress 0/3Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Law_of_small_numbersverified
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