When a coin toss does not appear random: Causal belief and judgments of randomness.

Abstract

Distinguishing between random and non-random data is important for inductive reasoning. Prior research has found a bias towards judging binary sequences with alternation rates above 0.5 as most random. In most of this research the concept of randomness was explained to participants via the example of a coin being tossed. The current experiment examined the influence of such example explanations on the perception of the randomness of binary sequences. Participants were told that sequences had been generated by a coin toss, a basketball player taking free throws, or were given no prior belief about the generating process (control). In the control condition there was no bias towards rating high alternation rate sequences as most random, however the bias persisted when a causal mechanism (coin, basketball player) was provided. Previously found correlations between perceived memorisability and perceived randomness were only found when a belief about the generating mechanism was provided.

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