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Other judgmental biases 263
Other judgmental biases
A large number of other biases in probability estimation have been
documented by researchers (see, for example, Hogarth and Makridakis 14
and Plous 7 ). We consider next two of these which are likely to be most
troublesome in the formulation of decision analysis models. A third
well-known bias, ‘conservatism’, will be discussed in Chapter 14.
1. Believing desirable outcomes are more probable
Much research has suggested that people tend to view desirable outcomes
as more probable than those which are undesirable. In one study 15
college students were asked to estimate how likely they were, relative
to other students of the same age and sex, to experience various positive
and negative events in their lives. Typically, students considered that
they were 15% more likely to experience positive events, such as owning
their own home, but 20% less likely to have negative events in their lives,
such as suffering a heart attack before they reached the age of 40.
2. Biased assessment of covariation
Earlier in the chapter we discussed illusory correlation and Tversky and
Kahneman’s explanation that people often see non-existent associations
between events because they can easily recall or imagine the events
occurring together. Several researchers have found that a similar bias
can occur when people are presented with tables showing the number
of times that events either occurred or failed to occur together. Consider,
for example, the problem of estimating the probability that a patient
has a disease, given that a particular symptom is present. Suppose that
you are given the information below which is based in the records of
27 patients:
(No. of patients)
Illness present Illness absent
Symptom present 12 6
Symptom absent 6 3
Would you conclude that there is a relationship between the symptom
and the disease? Research by Arkes et al. 16 suggests that many people