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254 Biases in probability assessment
judge him to be representative of what salesmen are like, that is he fits
your stereotypical view of a salesman, then you would assume that his
chances of being a salesman are high. Similarly, the peaks and troughs
in your sales graph may appear to be typical and representative of what
you perceive to be a random pattern so you judge that it is unlikely that
there is a regular cycle in your sales.
Biases associated with the representativeness heuristic
1. Ignoring base-rate frequencies
If you find that only 10% of the delegates at your conference party were
sales people then this should clearly be considered when you estimate
the probability of Peter being a salesman. Unfortunately, judgments
based on how typical Peter is of salesmen make no reference to this
statistical information (or base-rate frequency). This tendency to ignore
base-rate frequencies was demonstrated by Tversky and Kahneman in a
series of experiments where subjects were asked to judge the probability
that individuals had particular occupations. Subjects were given both
base-rate information and a description of the person. The following
question is typical of those used in the experiments.
This is a brief personality description of Tom W written by a psychologist
when Tom was at his senior year at high school. Tom W is of high intelligence,
although lacking in true creativity. He has a need for order and clarity and for
neat and tidy systems in which every detail finds its appropriate place. His
writing is rather dull and mechanical, occasionally enlivened by somewhat
corny puns and by flashes of imagination of the sci-fi type. He has a strong
drive for competence. He seems to have little feel or sympathy for other people
and does not enjoy interacting with others. Self-centred, he nonetheless has a
deep moral sense. This personality description has been chosen, at random,
from those of 30 engineers and 70 social scientists. What is your probability
that Tom W is an engineer?
Subjects appeared to base their probability estimates only on how representative
Tom W seemed to be of an engineer and typically stated that
it was more probable that he was an engineer. The information that this
description had been selected from a population of which only 30% were
engineers was ignored. Other experiments by Tversky and Kahneman
showed that this tendency to ignore base rates prevailed even when the
descriptive information given was totally uninformative, though base
rates were properly utilized when no descriptions were given.