Belief in Mean Reversion and the Law of Small Numbers

Studies find that people systematically underestimate the likelihood of
streaks in a random sequence. In a canonical coin-tossing environment, this
paper shows that the evidence can be explained by a belief in mean reversion.
Such beliefs are represented as if the bias of the coin is history-dependent and
“self-correcting”. In a Bayesian inference setting, a belief in mean reversion
ensures that the agent never rules out the true parameter.

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