372 • CHAPTER 13 Reasoning and Decision Making
When Amos Tversky and Daniel Kahneman (1974) presented this question in an
experiment, more people guessed that Robert was a librarian. Apparently the descrip-
tion of Robert as wearing glasses, speaking quietly, and reading a lot matched these
people’s image of a typical librarian (see illusory correlations, above). Thus, they were
infl uenced by the representativeness heuristic into basing their judgment on how closely
they think the characteristics used to describe Robert (A in our defi nition of the rep-
resentativeness heuristic) match those of a “typical” librarian (class B). However, they
were ignoring another important source of information—the base rates of farmers and
librarians in the population. The base rate is the relative proportion of different classes
in the population. In 1972, when this experiment was carried out, there were many more
male farmers than male librarians in the United States, so it is much more likely that
Robert was a farmer (remember that he was randomly chosen from the population).
One reaction to the farmer–librarian problem might be that perhaps the partici-
pants were not aware of the base rates for farmers and librarians, so they didn’t have
the information they needed to make a correct judgment. The effect of knowing the base
rate has been demonstrated by presenting participants with the following problem:In a group of 100 people, there are 70 lawyers and 30 engineers. What is the chance that
if we pick one person from the group at random that the person will be an engineer?Participants given this problem correctly guessed that there would be a 30 percent
chance of picking an engineer. However, for some participants, the following descrip-
tion of the person who was picked was added:Jack is a 45-year-old man. He is married and has four children. He is generally conserva-
tive, careful, and ambitious. He shows no interest in political and social issues and spends
most of his free time on his many hobbies, which include home carpentry, sailing, and
mathematical puzzles.Adding this description caused participants to greatly increase their estimate of
the chances that the randomly picked person (Jack, in this case) was an engineer.
Apparently, when only base rate information is available, people use that information
to make their estimates. However, when any descriptive information is available, people
disregard the base rate information, and this can potentially cause errors in reasoning.
Note, however, that the right kind of descriptive information can increase the accu-
racy of a judgment. For example, if the description of Jack also noted that his last job
involved determining the structural characteristics of a bridge that was being built, then
this would greatly increase the chance that he was, in fact, an engineer. Thus, just as
it is important to pay attention to base rate information, the information provided by
descriptions can also be useful if it is relevant. When such information is available, then
applying the representativeness heuristic can lead to correct judgments.Making Judgments Without Considering the Conjunction Rule The following dem-
onstration illustrates another characteristic of the representativeness heuristic.Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a stu-
dent, she was deeply concerned with issues of discrimination and social justice, and also par-
ticipated in antinuclear demonstrations. Which of the following alternatives is more probable?- Linda is a bank teller.
- Linda is a bank teller and is active in the feminist movement.
The correct answer to this problem is that Statement 1 has a greater probability of
being true, but when Tversky and Kahneman (1983) posed this problem to their partici-
pants, 85 percent picked Statement 2. It is easy to see why they did this. They were infl u-
enced by the representativeness heuristic, because the description of Linda fi ts people’sCopyright 2011 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part.