Abstract
Human randomness perception is commonly described as biased. This is because when generating random sequences humans tend to systematically under- and overrepresent certain subsequences relative to the number expected from an unbiased random process. In a purely theoretical analysis we have previously suggested that common misperceptions of randomness may actually reflect genuine aspects of the statistical environment, once cognitive constraints are taken into account which impact on how that environment is actually experienced (Hahn & Warren, Psychological Review, 2009). In the present study we undertake an empirical test of this account, comparing human-generated against unbiased process-generated binary sequences in two experiments. We suggest that comparing human and theoretically unbiased sequences using metrics reflecting the constraints imposed on human experience provides a more meaningful picture of lay people’s ability to perceive randomness. Finally, we propose a simple generative model of human random sequence generation inspired by the Hahn and Warren account. Taken together our results question the notion of bias in human randomness perception.
Highlights
ObjectivesThe purpose of the present study was to investigate the theoretical account of randomness perception put forward by Hahn and Warren (2009)
A Generative Model of Human Random Sequence Generation In Section 4 we presented a very simple generative model of how humans might produce random sequences
No evidence we present in the present manuscript can argue against the clear departures of human behavior from that which might be expected from an idealized information processing system
Summary
The purpose of the present study was to investigate the theoretical account of randomness perception put forward by Hahn and Warren (2009)
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