Watch for
Drawing firm conclusions from small samples.
Belief & ConfidenceBias #115
Law of Small Numbers
We expect small samples to represent the whole population.
The tendency to expect small statistical samples to mirror the exact properties and distribution of the broader population leading to overgeneralisation.
Why it matters: Tversky and Kahneman classic study. A fundamental concept in statistical thinking.
Try this
Check sample size before drawing conclusions. Larger samples are more reliable.
Real-world example
Three friends loving a new restaurant is taken as proof the restaurant is excellent ignoring the hundreds of other customers.
Key researchers
Amos Tversky, Daniel Kahneman
First described in 1971
Psychological mechanism
Representativeness heuristic. Small samples feel representative because they are vivid and available. The brain fails to account for sampling variability which is a statistical abstraction requiring System 2.
Seminal research
Amos Tversky and Daniel Kahneman (1971), "Belief in the law of small numbers."
Related Biases
Debrief
Biases are not character flaws. They are recurring patterns in how minds compress uncertainty, save energy, and narrate reality. Once you recognise the pattern, you can slow the decision down, test the assumption, and make space for a better explanation.
Sources
Original ResearchTversky and Kahneman (1971) — Law of small numbers
EducationalAPA Dictionary entry