Kahneman and Tversky singled out a major ineptitude in our Bayesian reasoning: we neglect the base rate, which is usually the best estimate of the prior probability.5 In the medical diagnosis problem, our heads are turned by the positive test result (the likelihood) and we forget about how rare the disease is in the population (the prior). The duo went further and suggested we don’t engage in Bayesian reasoning at all. Instead we judge the probability that an instance belongs to a category by how representative it is: how similar it is to the prototype or stereotype of that category, which we
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