Are humans good intuitive statisticians after all? Rethinking some conclusions from the literature on judgment under uncertainty.

摘要: Abstract Professional probabilists have long argued over what probability means, with, for example, Bayesians arguing that probabilities refer to subjective degrees of confidence and frequentists the frequencies events in world. Recently, Gigerenzer his colleagues these same distinctions are made by untutored subjects, that, many domains, human mind represents probabilistic information as frequencies. We analyze several reasons why, from an ecological evolutionary perspective, certain classes problem-solving mechanisms should be expected represent Then, using a problem famous “heuristics biases” literature eliciting base rate neglect, we show correct Bayesian reasoning can elicited 76% subjects - indeed, 92% most ecologically valid condition simply expressing frequentist terms. This result adds growing body showing representations cause various cognitive biases disappear, including overconfidence, conjunction fallacy, base-rate neglect. Taken together, new findings indicate conclusion common on judgment under uncertainty our inductive do not embody calculus will re-examined. From humans may turn out good intuitive statisticians after all.