Understanding Psychology (10th Ed)

particular concept. For 
example, a Prius might be a 
prototype of the concept of 
“hybrid car.”
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248 Chapter 
8 
Cognition and Language
A major technique for studying syllogistic reasoning involves asking people to 
evaluate a series of statements that present two assumptions, or premises, that are 
used to derive a conclusion. For example, consider the following syllogism:
Premise 1
All professors are mortal.
Premise 2
Dr. Rivera is a professor.
Conclusion Therefore, Dr. Rivera is mortal.
Because both premises are true, by applying logic appropriately we come to an 
accurate conclusion. More abstractly, we can state the syllogism as the following:
Premise 1
All A’s are B.
Premise 2
C is an A.
Conclusion
Therefore, C is a B.
However, even if the premises are correct, people may apply logic incorrectly. 
For example, consider the following syllogism:
Premise 1
All A’s are B.
Premise 2
C is an A.
Conclusion
Therefore, all A’s are C.
Although it may not be immediately apparent, the conclusion is illogical—
something we will see more readily if we make the syllogism more concrete:
Premise 1
All professors are mortal.
Premise 2
Professor Rivera is a professor.
Conclusion
Therefore, all professors are Dr. Rivera.
In short, syllogistic reasoning is only as accurate as the premises and the validity 
of the logic applied to the premises.
 ALGORITHMS AND HEURISTICS 
When faced with making a decision, we often turn to various kinds of cognitive 
shortcuts, known as algorithms and heuristics, to help us. An  algorithm  is a rule 
that, if applied appropriately, guarantees a solution to a problem. We can use an 
algorithm even if we cannot understand why it works. For example, you may know 
that you can fi nd the length of the third side of a right triangle by using the formula 
a
2
1
b
2
5
c
2
, although you may not have the foggiest notion of the mathematical 
principles behind the formula.
For many problems and decisions, however, no algorithm is available. In those 
instances, we may be able to use heuristics to help us. A  heuristic  is a thinking strategy 
that may lead us to a solution to a problem or decision, but—unlike algorithms—may 
sometimes lead to errors. Heuristics increase the likelihood of success in coming to a 
solution, but, unlike algorithms, they cannot ensure it. For example, when I play 
tic-tac-toe, I follow the heuristic of placing an X in the center square when I start the 
game. This tactic doesn’t guarantee that I will win, but experience has taught me that 
it will increase my chances of success. Similarly, some students follow the heuristic of 
preparing for a test by ignoring the assigned textbook reading and only studying their 
lecture notes—a strategy that may or may not pay off.
Although heuristics often help people solve problems and make decisions, cer-
tain kinds of heuristics may lead to inaccurate conclusions. For example, we some-
times use the representativeness heuristic, a rule we apply when we judge people by 
the degree to which they represent a certain category or group of people. Suppose, 
for instance, you are the owner of a fast-food store that has been robbed many times 
by teenagers. The representativeness heuristic would lead you to raise your guard 
each time someone of this age group enters your store (even though, statistically, it 
is unlikely that any given teenager will rob the store) (Fisk, Bury, & Holden, 2006; 
Nilsson, Juslin, & Olsson, 2008).