1. PSY 323 – Cognition
Chapter 13:
Judgment, Decisions & Reasoning

2. Making Judgments Inductive conclusions Are very broad
They are probably true based on evidence
Not definitely true, though
Specific observations
Crows in Washington are black
All crows are black
Broad conclusion

3. Inductive Reasoning
You do not judge inductive conclusions based on validity, but on strength (strength is subjective)
For example:
Representativeness of observations
Number of observations
Quality of the evidence

4. The Availability Heuristic
We use our memory of actual instances for our judgment. So, when we make a judgment, things that are available in our mind determine our judgment.
Tversky & Kahneman (1973)
Asked participants:
Think of words that begin with r.
Think of words that have r in the third position?
Which is easier to think of?

5. The Availability Heuristic
Results
70% said more words started with r
This despite the fact that there are three times as many words with r in the third position (car, park, barren, march)
Interpretation
Words that begin with r are more available to our memory
Tversky & Kahneman (1973)

6. The Availability Heuristic
Which cause of death do you consider to be more likely for people in the US? That is, if you randomly picked someone would they be more likely to die from cause A or cause B?
A B
Homicide or Appendicitis
Auto-train collision or Drowning
Botulism or Asthma
Asthma or Tornado
Appendicitis or Pregnancy
Lichtenstein et al. (1978)

7. The Availability Heuristic
Results 
Lichtenstein et al. (1978)

8. Availability: Illusory Correlations
Chapman & Chapman (1969)
Illusory Correlations
We think things are correlated, but they are not
A stereotype about the characteristics of a particular group may lead people to pay particular attention to behaviors associated with that stereotype, and this attention creates an illusory correlation that reinforces the stereotype
This phenomenon is related to the availability heuristic because selective attention to the stereotypical behaviors make these behaviors more “available”

9. The Representativeness Heuristic
Making judgments based on resemblance
The probability that A is a member of class B can be determined by how well the properties of A resembles the properties we usually associate with class B

10. The Representativeness Heuristic
Tversky & Kahneman (1974)
These researchers presented this example to participants:
We randomly pick one male from the population of the US. He wears glasses, speaks quietly, and reads a lot. Is it more likely that this male is a librarian or a construction worker?
Amos Tversky
Daniel Kahneman

11. The Representativeness Heuristic
Results
Most selected male librarian
Interpretation
Representativeness heuristic: Properties of an object determine its class with little regard for probability in the population (base rate)
Tversky & Kahneman (1974)

12. The feminist bank teller
Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with the issues of discrimination and social justice. Which of the following is more probable?
Linda is a bank teller.
Linda is a bank teller and is active in the feminist movement.
Tversky & Kahneman (1983)

13. What did you choose?
Most participants choose the second one, even though they’re more likely right by choosing the first one
Conjunction Rule 
People ignore the conjunction rule:
P(two events) < P(one of the two events)

14. The problem of small samples…
A certain town has two hospitals. The large hospital has ~45 babies born a day, and the small hospital has ~15 births a day. About 50% of all babies are boys. However, the exact percentage varies by day. For a period of 1 year, each hospital recorded the days on which more than 60% of babies born were boys.
Which hospital recorded more of these days?
Tversky & Kahneman (1974)

15. What’s the answer? The small hospital
Why? Law of large numbers - The more samples you take, the more representative the resulting group will be

16. The Confirmation Bias Wason (1960)
A tendency to selectively look for information that conforms to our hypothesis and to overlook information that argues against it
Very strong effect
Can cause us to ignore relevant information

17. Decision Making: Choosing among alternatives
How do we choose?
Utility
Outcomes that are desirable are in the person’s best interest; outcomes that achieve a person’s goals
Expected utility theory
Assumes people are rational when making decisions
However, this doesn’t always hold true
See next slide 

18. Decision Making: Choosing among alternatives
Denes-Raj & Epstein (1994)
Researchers offered participants the opportunity to earn up to $7 by receiving $1 every time they drew a red jelly bean
Many participants chose the larger bowl with the less favorable probability

19. Problems with the utility approach…
People are not good at predicting their emotional utility
Predicting the utility (how much satisfaction you would get) of one choice over the other isn’t that easy
Many psychological factors influence your perception of utility

20. How emotions affect decisions..
Immediate emotions
Integral immediate emotions
Emotions that are associated with the act of decision-making
Incidental immediate emotions
Emotions unrelated to the decision yet can still affect the decision

21. Decisions can depend on how choices are presented
Slovic et al. (2000)
Wording of a problem can affect the decision
See Mr. Jones example on p. 384

22. Decisions can depend on how choices are presented
Framing Effect
Tversky & Kahneman (1981)
Presented participants with the following scenario:
Imagine that the US is preparing for the outbreak of an unusual disease that is expected to kill 600 people. Two alternatives programs to combat the disease have been proposed. Assume that the exact scientific estimates of the consequences of the programs are as follows.
If Program A is adopted, 200 people will be saved.
If Program B is adopted, there is a 1/3 probability that 600 people will be saved, and a 2/3 probability that no people will be saved.
Which program would you choose?

23. Presented participants with the following scenario:
Two alternatives programs to combat the disease have been proposed. Assume that the exact scientific estimates of the consequences of the programs are as follows.
If Program C is adopted, 400 people will die.
If Program D is adopted, there is a 1/3 probability that nobody will die, and a 2/3 probability that 600 people will die.
Which program would you choose?
Tversky & Kahneman (1981)

24. Framing Effect
Results 
Tversky & Kahneman (1981)

25. Two strategies were employed…
Risk-aversion strategy
Program A: The idea of saving 200 lives with certainty is more attractive than the risk that no one will be saved
Risk-taking strategy
Program D: The idea of losing 400 lives with certainty is less attractive than the risk that a 2 in 3 chance that 600 people will die
Tversky & Kahneman (1981)

26. Framing Effect Example:
If you are lucky, you have a chance to win $1000. Which game do you choose?
Game A. a sure gain of $250
Game B. 25% chance to gain $1000 and 75% chance to gain nothing
Game A  84%
Game B  16%
Tversky & Kahneman (1981)

27. Framing Effect Example:
You are given $1000, provided that you will play either one of the following games. Which game do you choose?
Game C. a sure loss of $750
Game D. 75% chance to lose $1000 and 25% chance to lose nothing.
Game C.  13%
Game D.  87%
Tversky & Kahneman (1981)

28. Deductive Reasoning: Syllogism & Logic
Deductive conclusions
Are very specific from a sequence of statements called syllogisms
Logical conclusions
All birds are animals
All animals eat food
Broad statements - premises
All birds eat food
Specific conclusion

29. Deductive Reasoning: Syllogism & Logic
Categorical Syllogisms
The relationship between two categories is described by using statements that begin with all, no, or some.
All birds are animals. (All A are B)
All animals have four legs. (All B are C)
All birds have four legs. (All A are C)

30. Validity & Truth in Syllogisms
Premise
Two statements that precede the conclusion
Conclusion
A third statement that follows the premises
Validity
A syllogism is valid when its conclusions follows logically from its two premises (deductive reasoning)

31. Conditional Syllogisms
Conditional reasoning is reasoning about propositions using the logical relation known as implication
Formally, it is based on propositional logic
‘if….then’, ‘if…& only if’ (also not, and, and or are used in propositional logic)
Example:
If I study, I’ll get a good grade.
I studied
Therefore, I’ll get a good grade.

32. Conditional Reasoning: Wason Selection Task
Rule: If there is a vowel on one side of a card, then there is an even number on the other.
Question: Which card(s) do you need to turn over to test that this rule is true for these four cards?
Approximately 4% of people (university students) get this right on their first try. E K 4 7

33. Conditional Reasoning
Griggs & Cox (1982)
Found that real-life concrete information helps your reasoning
See next slide 

34. Each card has an age on one side and the name of a beverage on the other side.
Indicate the minimum number of cards you need to turn over to test that the following rule is true for all four cards:
If a person is drinking beer, then he or she must be over 19 years old.
Griggs & Cox (1982)

35. Conditional Reasoning
Griggs & Cox (1982)
Answer
You have to turn beer and 16 years old
Results
73% of the participants were correct with concrete version; none with abstract

36. Conditional Reasoning
Interpretation
Why is there such a big difference in the two problems?
People use a pragmatic (real-life) reasoning schema to solve a these problems
A way of thinking about cause and effect in the world that is learned as part of experiencing everyday life
Permission schema is an example
Only if something is satisfied, you can do something else

37. Credits
Some of the slides in this presentation prepared with the assistance of the following web sites:
archlab.gmu.edu/people/jthompsz/11-ReasoningDecisionMaking_2.ppt
ftp:// /pub/fred/teaching/Cog_Psych_8.ppt