The Law of Small Numbers
Chapter summary from Thinking, Fast and Slow by Daniel Kahneman.
Small samples tempt you into strong stories. A few observations feel like evidence of a pattern, especially when the pattern is vivid.
But randomness is noisy. In small samples, extremes are common, and apparent regularities are often just fluctuation. The mind prefers a narrative of cause.
This creates overconfidence in early results—especially in research, business, and personal judgment—where the first runs of data look persuasive. You start explaining variance as if it were destiny.
The slow system knows the math, yet intuition keeps treating small samples as representative. You expect balance too early, and you see signals in static.
The correction is structural: demand larger samples, consider base rates, and treat striking early outcomes as provisional, not prophetic.
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