“a shy poetry lover” : I borrowed this example from Max H. Bazerman and
Don A. Moore, Judgment in Managerial Decision Making (New York:
Wiley, 2008).
always weighted more : Jonathan St. B. T. Evans, “Heuristic and Analytic
Processes in Reasoning,” British Journal of Psychology 75 (1984): 451–
68.
the opposite effect : Norbert Schwarz et al., “Base Rates,
Representativeness, and the Logic of Conversation: The Contextual
Relevance of ‘Irrelevant’ Information,” Social Cognition 9 (1991): 67–84.
told to frown : Alter, Oppenheimer, Epley, and Eyre, “Overcoming Intuition.”
Bayes’s rule : The simplest form of Bayes’s rule is in odds form, posterior
odds = prior odds × likelihood ratio, where the posterior odds are the odds
(the ratio of probabilities) for two competing hypotheses. Consider a
problem of diagnosis. Your friend has tested positive for a serious
disease. The disease is rare: only 1 in 600 of the cases sent in for testing
actually has the disease. The test is fairly accurate. Its likelihood ratio is
25:1, which means that the probability that a person who has the disease
will test positive is 25 times higher than the probability of a false positive.
Testing positive is frightening news, but the odds that your friend has the
disease have risen only from 1/600 to 25/600, and the probability is 4%.
For the hypothesis that Tom W is a computer scientist, the prior odds
that correspond to a base rate of 3% are (.03/. 97 = .031). Assuming a
likelihood ratio of 4 (the description is 4 times as likely if Tom W is a
computer scientist than if he is not), the posterior odds are 4 ×. 031 =
12.4. From these odds you can { odes as l compute that the posterior
probability of Tom W being a computer scientist is now 11% (because
12.4/112. 4 = .11).

15: Linda: Less is More

the role of heuristics : Amos Tversky and Daniel Kahneman, “Extensional
Versus Intuitive Reasoning: The Conjunction Fallacy in Probability
Judgment,” Psychological Review 90(1983), 293-315.
“a little homunculus” : Stephen Jay Gould, Bully for Brontosaurus (New
York: Norton, 1991).
weakened or explained : See, among others, Ralph Hertwig and Gerd
Gigerenzer, “The ‘Conjunction Fallacy’ Revisited: How Intelligent Inferences
Look Like Reasoning Errors,” Journal of Behavioral Decision Making 12
(1999): 275–305; Ralph Hertwig, Bjoern Benz, and Stefan Krauss, “The
Conjunction Fallacy and the Many Meanings of And,” Cognition 108