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266 Biases in probability assessment
situations sales do not continue to increase at the same rate; instead the
rate of increase lessens as the market ceiling is approached.
4. Subjects may be poorly motivated
As we indicated earlier, many psychological studies have involved
undergraduates as subjects. Where these subjects lacked expertise relating
to the experimental task, this may also have affected motivation. As
Beach et al. point out, the effort which subjects are prepared to invest in
a judgmental task is likely to be reduced if the task is not perceived to be
within their own particular area of expertise. Also, the absence of actual
or potential users of probability judgments made in the laboratory may
serve to reduce motivation. 24 Moreover, in many studies there were no
rewards for good judgment so that there may have been little incentive to
reflect deeply on the task. This is unlikely to be the case in a real decision
where your income, reputation, job or even your life may depend upon
the quality of your judgments.
5. Citation bias
Beach et al. 19 identified what they termed a ‘citation bias’ in the psychological
literature. Of the 3500 articles on judgment and reasoning
published between 1972 and 1981 only 84 were empirical studies. Of
these, 47 reported poor performance and 37 found good performance.
However, poor performance results were cited by authors on average
six times more often than were results showing good performance.
6. Real-world studies suggest better performance
Relatively little research has focused on probability judgments made in
real decisions. The most extensive studies have been carried out on the
judgmental probability forecasts made by the National Weather Service
in the United States. Murphy and colleagues 24 have evaluated these
probabilities and found that, for certain categories of weather, they were
more accurate than the available objective statistical techniques (accuracy
here is measured by the calibration of the probabilities, see Chapter 10,
and by special scoring rules 25 ). In this case, the forecasters have a
very large amount of information available, including the output from
statistical techniques. They also receive detailed feedback and have an
opportunity to gain experience of making forecasts over a wide range of