The document discusses various models of decision making and reasoning, including classical decision theory, heuristics and biases, deductive reasoning through conditional statements and syllogisms, and inductive reasoning using observations to draw probable but not certain conclusions. Judgment is influenced by heuristics like availability and representativeness, and people tend to overestimate their abilities.

1. Decision Making and
Reasoning
Chapter 12

2. Outline
1. Judgment and Decision Making
1. Classical Decision Theory
2. Satisficing
3. Elimination by Aspects
4. Heuristics and Biases
2. Deductive Reasoning
1. Conditional Reasoning
3. Inductive Reasoning

3. 1. Judgment and Decision Making
• The goal of judgment and decision making is to
select from among choices or to evaluate
opportunities
1. Classical Decision Theory
• Based on the assumption or rationality
– People make their choices so as to maximize
something of value, whatever that something may be
• Mathematical models of human decision making
– Too restricted, does not take into account the
psychological makeup of each individual decision
maker

4. 1. Judgment and Decision Making
1. Classical Decision Theory
• Subjective expected utility theory
– The goal of human action is to seek pleasure
and avoid pain; in doing so each of us uses
calculations of
• Subjective utility – based on the individual’s judged
weightings of utility, rather than on objective
criteria
• Subjective probability – based on the individual’s
estimates of likelihood, rather than on objective
statistical computations

5. 1. Judgment and Decision Making
1. Classical Decision Theory
• This theory is based on the belief that people
seek to reach well-reasoned decisions based on
– Consideration of all possible known alternatives
– Use of a maximum amount of available information
– Careful weighing of costs and benefits and calculation
of probability
– A maximum degree of sound reasoning
• However, human decision making is more
complex than even this modified theory implies

6. 1. Judgment and Decision Making
2. Satisficing
• We humans are not entirely and boundlessly
rational in making decisions
• Bounded rationality
– We are rational, but within limits
• Satisficing
– We do not consider all possible options and then
carefully compute which of the entire universe of
options will maximize our gains and minimize our
losses
– Rather, we consider options one by one, and then we
select an option as soon as we find one that is
satisfactory or just good enough to meet our minimum
level of acceptability

7. 1. Judgment and Decision Making
3. Elimination by Aspects
• We sometimes use a different strategy when
faced with far more alternatives than we feel that
we reasonably can consider in the time we have
available
• Elimination by aspects
– We focus on one aspect (attribute) of the various
options, and we form a minimum criterion for that
aspect
– We then eliminate all options that do not meet that
criterion

8. 1. Judgment and Decision Making
4. Heuristics and Biases
• Amos Tversky and Daniel Kahneman
– People may be far more likely to make
decisions based on biases and heuristics
(short-cuts) than earlier decision-making
research has suggested
– These mental shortcuts lighten the cognitive
load of making decisions, but they also allow
for a much greater chance of error

9. ?
All the families having exactly six children in
a particular city were surveyed. In 72 of
the families, the exact order of births of
boys and girls was GBGBBG (G girl; B
boy).
What is your estimate of the number of
families surveyed in which the exact order
of births is BGBBBB?

10. 1. Judgment and Decision Making
4. Heuristics and Biases
• Representativeness
– When we use the heuristic of representativeness, in
which we judge the probability of an uncertain event
according to
• (1) how obviously it is similar to or representative of the
population from which it is derived
• (2) the degree to which it reflects the salient features of the
process by which it is generated
• Example on the previous slide
– First birth order is considered to be more
representative of the number of females and males in
the population
– However, either birth order is equally likely to occur by
chance

11. ?
Are there more words in the English
language that begin with the letter R or
that have R as their third letter?

12. ?
• Calculate in your head the answer to the
following problem:
8x7x6x5x4x3x2x1

13. ?
• Calculate in your head the answer to the
following problem:
1x2x3x4x5x6x7x8

14. 1. Judgment and Decision Making
4. Heuristics and Biases
• Availability
– We make judgments on the basis of how easily we
can call to mind what we perceive as relevant
instances of a phenomenon (e.g. words beginning
with letter R)
• Anchoring-and-adjustment heuristic
– People provide a higher estimate for the first
sequence than for the second because their
computation for the the anchor – the first few digits
multiplied by each other – renders a higher estimate
from which they make an adjustment to reach a final
estimate

15. 1. Judgment and Decision Making
4. Heuristics and Biases
• Overconfidence
– And individual’s overvaluation of her or his
own skills, knowledge, or judgments
– People tend to overestimate the accuracy of
their judgments
– Example:
• When people were 100% confident in their
answers, they were right only 80% of the time

16. 2. Deductive Reasoning
• Proposition
– An assertion, which may be either true of false
• Premise
– Propositions about which arguments are
made

17. 2. Deductive Reasoning
1. Conditional Reasoning
• The reasoner must draw a conclusion based on
an if-then proposition
• Deductive validity
– Does not equate with truth
– You can reach deductively valid conclusions that are
completely untrue with respect to the world
– People are more likely mistakenly to accept an
illogical argument as logical if the conclusion is
factually true

18. 2. Deductive Reasoning
1. Conditional Reasoning
• Modus ponens
– The reasoner affirms the antecedent
If p then q
p
q
• Modus tollens
– The reasoner denies the consequent
If p then q
non q
non p

19. 2. Deductive Reasoning
1. Conditional Reasoning
• Deductive fallacies
– Denying the antecedent
– Affirming the consequent
• Rather then using formal inference rules,
people often use pragmatic reasoning
schemas

20. 2. Deductive Reasoning
2. Syllogistic Reasoning
• Syllogisms
– Are deductive arguments that involve drawing
conclusions from two premises
– All syllogisms comprise a major premise, a
minor premise, and a conclusion

21. 2. Deductive Reasoning
2. Syllogistic Reasoning
• Linear Syllogisms
– The relationship among the terms is linear,
involving a quantitative or qualitative
comparison
– Example
• You are smarter than your best friend.
• Your best friend is smarter than your roommate.
• Which of you is the smartest?

22. 2. Deductive Reasoning
2. Syllogistic Reasoning
• Categorical Syllogisms
– Comprise of two premises and a conclusion
– The premises state something about the
category memberships of the terms
– Example:
• All cognitive psychologists are pianists.
• All pianists are athletes.
• Therefore, all cognitive psychologists are athletes.

23. 3. Inductive Reasoning
• In inductive reasoning, which is based on our
observations, reaching any logically certain
conclusion is not possible
• The most we can strive to reach is only a strong,
or highly probable, conclusion
• A key feature of inductive reasoning, which
forms the basis of the empirical method, is that
we cannot logically leap from saying, “ all
observed instances to date of X are Y” to saying,
“Therefore, all X are Y”; it is always possible that
the next observed X will not be a Y

24. 3. Inductive Reasoning
• Causal inferences
– How people make judgments about whether
causes something else
• Errors in inductive reasoning
– Confirmation bias
• Teachers often expect little of students when they
think them low in ability
– Causality based on correlational evidence
alone
• We fail to recognize many that many phenomena
have multiple causes

25. 3. Inductive Reasoning
• Reasoning by analogy
• Example
Fire is to asbestos as water is to
a. Vinyl
b. Air
c. Cotton
d. faucet