closed world

Terms from Statistics for HCI: Making Sense of Quantitative Data

A world where we assume we know everything and there are no unknown external factors. Bayesian statistics effectively uses a closed world assumption as it requires all unknown parameters to be assigned a prior probability. In contrast, traditional statistics adopts an open world model where some parameters are treated as completely unknown.

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