Errors in probability updating behaviour
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TL;DR
A model to measure this error in a consistent and comparable way is developed and it is found that the attributes of the messages influence the size of the errors.
Abstract
It is an empirical fact of life that decision makers make errors in probability updating. In this paper we develop a model to measure this error in a consistent and comparable way (i.e. across different cases the same scale of measurement is involved). In a laboratory experiment we test our model for the updating process of normal and beta distributions and find that indeed the participants show the expected deviations from Bayes' rule. In addition, we find that the attributes of the messages (precision, reliability, relevance, timeliness) influence the size of the errors.PsycINFO classification: 2343
