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Chapter 12: Decision Making and Reasoning

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Chapter 12: Decision Making and Reasoning * Koehler, J.J. (1996). The base rate fallacy reconsidered: Descriptive, normative, and methodological challenges. – PowerPoint PPT presentation

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Title: Chapter 12: Decision Making and Reasoning


1
Chapter 12 Decision Making and Reasoning
2
Decision Making
  • 2 different types of models for decision making
  • Prescriptive models
  • Models describing the best way to make a decision
  • Descriptive models
  • Models describing the way decisions are actually
    made
  • Cognitive psychologists are interested in how
    people actually make decisions

3
Classical Decision Theory
  • Assumed decision makers
  • Knew all the options available
  • Understood pros and cons of each option
  • Rationally made their final choice
  • Goal was to maximize value of decision

4
Howards Dilemma
  • Thagard Milgram (1995)
  • An eminent philosopher of science once
    encountered a noted decision theorist in a
    hallway at their university. The decision
    theorist was pacing up and down, muttering, What
    shall I do? What shall I do?
  • What's the matter, Howard? asked the
    philosopher.
  • Replied the decision theorist, It's horrible,
    Ernest - I've got an offer from Harvard and I
    don't know whether to accept it.
  • Why Howard, reacted the philosopher, you're
    one of the world's great experts on decision
    making. Why don't you just work out the decision
    tree, calculate the probabilities and expected
    outcomes, and determine which choice maximizes
    your expected utility?
  • With annoyance, the other replied, Come on,
    Ernest. This is serious.

5
Subjective Utility Theory
  • Goal
  • Seek pleasure and avoid pain
  • Actual judgment of pleasure and pain is made by
    each decision maker (subjective)

6
Subjective Expected Utilities
  • Consider all possible alternatives
  • Use all information currently known
  • Weigh potential costs and benefits
  • Subjective weighing of various outcomes
  • Sound reasoning consider above factors

7
Satisficing
  • To obtain an outcome that is good enough
  • Term introduced by Herbert A. Simon in his Models
    of Man 1957
  • Simon noted that humans are rational but within
    limits (bounded rationality)

8
Elimination by Aspects
  • Tversky (1972)
  • Begin with a large number of options
  • Determine the most important attribute and then
    select a cutoff value for that attribute
  • All alternatives with values below that cutoff
    are eliminated
  • The process continues with the most important
    remaining attribute(s) until only one alternative
    remains

9
Group Decision Making
  • Can enhance decision making
  • More ideas
  • Better memory of events

10
Disadvantage of Group Decisions
  • Groupthink
  • Premature decision made by members trying to
    avoid conflict

11
Symptoms of Groupthink
  • Closed-mindedness
  • Rationalization
  • Squelching of dissent
  • Formation of mindguard
  • Feeling invulnerable

12
Heuristics Influencing Decision Making
  • Representativeness
  • Availability
  • Anchoring adjustment
  • Overconfidence
  • Illusory correlation
  • Hindsight bias

13
Making Decisions
  • Chris is 67, 300 pounds, has 12 tattoos, was a
    champion pro wrestler, owns nine pit bulls and
    has been arrested for beating a man with a chain.
  • Is Chris more likely to be a man or a woman?
  • A motorcycle gang member or a priest?
  • How did you make your decision?

14
Making Decisions
  • Steve is meek and tidy, has a passion for detail,
    is helpful to people, but has little real
    interest in people or real-world issues.
  • Is Steve more likely to be a librarian or a
    salesperson?
  • How did you come to your answer?

15
Making Decisions
  • Linda is a 31-year-old, single, outspoken, and
    very bright person. She majored in philosophy.
    As a student, she was deeply concerned with
    issues of discrimination and social justice, and
    also participated in antinuclear demonstrations.
  • What is the probability that Linda is a bank
    teller?
  • What is the probability that Linda is a feminist
    bank teller?

16
Representativeness Heuristic
  • Judge probability of an event based on how it
    matches a stereotype
  • Can be accurate
  • Can also lead to errors
  • Most will overuse representativeness
  • i.e. Steves description fits our vision of a
    librarian, Linda seems to be more of a feminist

17
Representativeness Heuristic
  • Gamblers Fallacy
  • Mistaken belief that a random event is affected
    by previous random events
  • Believe that your turn to win has come
  • In reality, probability to win is still same
    probability

18
Base rate Information
  • The actual probability of an event
  • How many bank tellers are there in the world?
  • How many feminists are there?
  • Much research in the 1970s 1980s seemed to
    indicate that base rate information in these type
    of problems were ignored
  • Current research focuses on when participants do
    pay attention to base rates

19
Koehler (1996)
  • Base rates are used when
  • Problems are written in ways that sensitize
    decision-makers to the base rate
  • Problems are conceptualized in relative frequency
    terms
  • Problems contain cues to base rate diagnosticity
  • Problems invoke heuristics that focus attention
    on the base rate

20
Making Decisions
  • Which are you more afraid of?
  • Flying in an airplane
  • Driving in a car
  • Meyers (2001)
  • The Air Transport Association reports that 483
    passengers were killed in plane crashes from
    1995-1999 (97 per year). During these years, the
    National Safety Council's Research and Statistics
    Department tells me, we were 37 times safer per
    passenger mile in planes than motor vehicles.

21
Availability Heuristic
  • Making judgments about the frequency or
    likelihood of an event based on how easily
    instances come to mind
  • Actual frequency influences how easily evidence
    comes to mind but so do other factors
  • Media
  • Vividness

22
Schwartz (1991)
  • Manipulated how many instances participants had
    to give of previously being assertive
  • One group had to recall six examples of when they
    had been assertive
  • A second group had to think of twelve examples
  • Both groups were then asked to score their
    assertiveness
  • Participants who thought of six examples scored
    themselves higher than the group that had
    difficulty thinking of twelve examples
  • Pattern of results attributed to the availability
    heuristic

23
Anchoring-and-Adjustment Heuristic
  • Begin by guessing a first approximation (an
    anchor)
  • Make adjustments to that number on the basis of
    additional information
  • Often leads to a reasonable answer
  • Can lead to errors in some cases

24
Anchoring-and-Adjustment
  • People are influenced by an initial anchor value
  • Anchor value may be unreliable, irrelevant, and
    adjustment is often insufficient

25
Anchoring-and-Adjustment
  • Participants asked to calculate in 5 secs the
    answer to one of the following problems
  • 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 512
  • 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 2,250
  • The order of presentation for these two groups
    had a significant impact on their estimates
  • The correct answer, in both cases, is 40,320!

26
Effect of Framing on Decisions
  • Which choice would you make?
  • Suppose you have invested in stock equivalent to
    the sum of 60,000 in a company that just filed a
    claim for bankruptcy. They offer two
    alternatives in order to save some of the
    invested money
  • If Program A is adopted, 20,000 will be saved
  • If Program B is adopted, there is a 1/3
    probability that 60,000 will be saved and a 2/3
    probability that no money will be saved

27
Rönnlund, Karlsson, Laggnäs, Larsson, Lindström
(2005)
  • Examined the impact of framing on risky decisions
  • Manipulated age (young/older) and type of framing
    (positive/negative)
  • Participants read one of 3 scenarios
  • Participants selected either a risky or certain
    outcome

28
Sample Scenario
  • Suppose you have invested in stock equivalent to
    the sum of 60,000 in a company that just filed a
    claim for bankruptcy. They offer two
    alternatives in order to save some of the
    invested money
  • Positive Framing
  • If Program A is adopted, 20,000 will be saved
    (certain outcome)
  • If Program B is adopted, there is a 1/3
    probability that 60,000 will be saved and a 2/3
    probability that no money will be saved (risky
    outcome)
  • Negative Framing
  • If program A is adopted 40,000 will be lost
    (certain outcome)
  • If program B is adopted, there is a 1/3
    probability that no money will be lost, and 2/3
    probability that 60,000 will be saved (risky
    outcome)

29
Try It!
  • Write your name on a piece of paper and indicate
    the truth of the following statements
  • 1 means you are sure it is true, 10 means you are
    sure it is false

  Truth Rating
1. Martin Luther King was 39 when he died.  
2. The gestation period of an Asian elephant is 225 days.  
3. The earth is the only planet in the solar system that has one moon.  
4. The number of lightning strikes in the United states per year is 25 million.  
5.The Rhöne is the longest river in Europe.  
Collect the sheets.
30
Try It Answers
  • Martin Luther King was 39 when he died
  • The gestation period of an Asian elephant is not
    225 days--It is 645 days
  • The earth is the only planet in the solar system
    that has one moon. False, Pluto also has one moon
  • The number of lightning strikes in US is
    approximately 25 million
  • The Rhöne is not the longest river in Europe

31
Illusory Correlations
  • An illusory correlation is a perceived
    relationship that does not, in fact, exist
  • Illusory correlations are formed by the pairing
    of two distinctive events
  • Redelmeier and Tversky (1996)
  • 18 arthritis patients observed over 15 months
  • The weather was also recorded
  • Most of the patients were certain that their
    condition was correlated with the weather
  • The actual correlation was close to zero 
  • What illusory correlations may affect your
    decisions?

32
Demonstration- Future events
  • Predict whether you will experience these events
    this semester
  • Obtain an A in your favorite course.
  • Have an out-of-town friend visit you.
  • Lose more than ten pounds.
  • Drop a course after the 5th week.
  • Be the victim of a crime.
  • Get a parking or speeding ticket.
  • How confident are you of your judgment for each
    item? (100, 80, 60.....)

33
Overconfidence
  • People tend to have unrealistic optimism about
    their abilities, judgments and skills
  • Examine your confidence judgments about future
    events asked on a previous slideare you
    confident your judgments are accurate?

34
Dunn Story (1991)
  • Examined overconfidence of students
  • At beginning of the semester students were given
    37 items like the ones on the previous slide
  • At end of the semester, students were asked to
    indicate which events had actually occurred

35
Dunn Story (1991)
  • Results indicated that all students exhibited
    large tendencies toward overconfidence
  • Confidence influences how we make decisions, yet
    our confidence may not be based on a realistic
    estimate of events or skills
  • Why is this a problem?

36
Try it againPredict your past answer
1 means you were sure it was true 10 means you
were sure it was false
  Your past answer
1. Martin Luther King was 39 when he died.  
2. The gestation period of an Asian elephant is 225 days.  
3. The earth is the only planet in the solar system that has one moon.  
4. The number of lightning strikes in the United states per year is 25 million.  
5.The Rhöne is the longest river in Europe.  
37
Hindsight Bias
  • The memory of how we acted previously changes
    when we learn the outcome of an event

38
Hindsight Bias
  • Reconstruction after feedback theory (RAFT)
  • Proposed by Hoffrage,Hertwig Gigerenzer (2000)
  • Allows us to remove clutter by tossing out
    inaccurate information and embracing the right
    answers in our memory

39
Do People Reason Logically?
  • Deductive reasoning
  • Formal procedure that ensures accuracy if rules
    of logic are followed
  • Given some premises that are true, one can reach
    a conclusion that must also be true
  • Example
  • All men are mortal.
  • Socrates is a man.
  • Therefore, Socrates is mortal.

40
Deductive Validity
  • How do we know when an argument is valid?
  • Typically deductive arguments have three
    statements
  • If P, then Q (Conditional if-then statement)
  • Statement about whether P or Q is true or not
    true
  • A conclusion about P or Q

41
Two Valid Deductive Inferences
  • Modus Ponens
  • If P, then Q All fruit grows on trees
  • P is true An apple is a fruit
  • Q is true Therefore, apples grow on trees
  • Modus Tollens
  • If P, then Q All fruit grows on trees
  • Not Q Tomatoes do not grow on trees
  • Not P Therefore, tomatoes are not a fruit

42
Two Deductive Fallacies or Errors
  • Denying the antecedent
  • If P, then Q All fruit grows on trees
  • Not P Tomatoes are not a fruit
  • Not Q Therefore, tomatoes do not grow on
    trees
  • Affirming the consequence
  • If P, then Q All fruit grows on trees
  • Q Acorns grow on trees
  • P Acorns are fruit

43
Wason Card Selection Task
A
2
X
3
  • Each card has a letter on one side and a digit on
    the other. Determine by turning over the minimum
    number of cards if this rule is true If there is
    a vowel on one side, there is an even number on
    the other side.

44
Wason Selection Task
A
2
X
3
  • If vowel then even number on the other side
  • Must turn over A (Modus Ponens)
  • Most get this card right, confirmation bias
  • Because a vowel, want to see if even number of
    other side
  • Must turn over 3 (Modus Tollens)
  • Only 15 of college students get this correct
  • Must be sure there is not a vowel on the other
    side
  • 2 card doesnt matter
  • Rule does not state that all even numbers have to
    have vowels
  • X card doesnt matter.
  • Rule does not specify anything about consonants.

45
Syllogistic Reasoning
  • Statement 1 All men are animals
  • Statement 2 Some animals are aggressive
  • Conclusion Some men are aggressive
  •  
  • This seems to be a reasonable conclusion, but
    then consider the following 
  • Statement 1 All men are animals
  • Statement 2 Some animals are female
  • Conclusion Some men are female 
  • Now the conclusion appears to be ridiculous and
    false
  • - yet the reasoning is exactly the same as in the
    first example.
  • Thus, the first example has a false conclusion.
  • The animals who are aggressive are not
    necessarily men.

46
Griggs Cox (1982)
Beer
22
Coke
17
  • Four people are sitting at a table. Who do you
    question to determine whether the law is being
    broken? If a person is drinking beer, then the
    person must be 21 or over.

47
Pragmatic Reasoning Schema
  • Cheng Holyoak (1985)
  • Theorized a permission schema exists that helps
    to solve the problem
  • Once activated, the schema enables the person to
    determine what evidence is necessary to evaluate
    the rule
  • Activated by a context that involves permission
  • To use the pool, you must be a patron of the
    hotel

48
Cheng Holyoak (1985)
  • Reframed the Wason card selection task in the
    form of a permission statement
  • Found that 61 of college students now got the
    problem correct versus only 19 when the problem
    was not framed in terms of permission

49
Syllogistic Reasoning
  • Draw a conclusion based on two premises
  • A major premise
  • A minor premise
  • A conclusion

50
Syllogistic Reasoning
  • True Categorical Syllogism
  • False Categorical Syllogism
  • All men are animals
  • Some animals are aggressive
  • Some men are aggressive 
  • All men are animals
  • Some animals are female
  • Some men are female

The second conclusion appears to be ridiculous
and false - yet the reasoning is exactly the
same as in the first example. The first example
thus has a false conclusion. The animals who are
aggressive are not necessarily men
51
How do People Solve Syllogisms?
  • Mental Model
  • A mental model represents one possibility,
    capturing what is common to all the different
    ways in which the possibility may occur.
  • Mental models represent explicitly what is true,
    but not what is false. These characteristics may
    lead to systematic errors.

52
Working Memory and Syllogisms
  • Gilhooly Associates (1993)
  • Present syllogisms orally or visually
  • Oral presentation leads to heavier load on
    working memory
  • Participants in the oral presentation performed
    more poorly.

53
Obstacles to Deductive Reasoning
  • Overextension errors
  • Foreclosure errors
  • Confirmation bias

54
Enhancing Deductive Reasoning
  • Avoid heuristics and biases that distort our
    reasoning
  • Consider more alternatives
  • Training and practice
  • Being sad

55
Evolutionary View
  • Cosmides Tooby (1996)
  • Humans are social animals
  • Humans have evolved to deal well with social
    rules

56
Inductive Reasoning
  • Involves reasoning from specific cases to more
    general, but uncertain, conclusions
  • Cannot reach a conclusion with 100 accuracy
  • Can reach a highly probable outcome

57
How People Make Causal Inferences
  • John Stuart Mills Cannons
  • Method of Agreement
  • Method of Difference

58
Schustack Sternberg (1981)
59
Schustack Sternberg (1981) Results
  • Indicated 4 pieces of information were used to
    determine causality
  • Joint presence of possible cause and outcome
  • Joint absence of cause and outcome
  • If one was absent and other was present then no
    causality

60
Confirmation Bias
  • Tendency to search for and interpret evidence in
    a way that confirms our theories and avoid
    evidence that contradicts prior beliefs
  • E.g., Self-fulfilling prophecy

61
Deductive vs. Inductive Reasoning
  • Turvey (1999) provides example of each type of
    reasoning in a forensic context
  • Deductive reasoning
  • Fingerprint in blood is on knife
  • Fingerprint belongs to D
  • Therefore, D was in contact with knife after
    victim began to bleed
  • Inductive reasoning
  • 85 of known killers who use severe blunt force
    trauma to the faces of their victims live with
    their mother
  • 75 of known killers who tie up their victims
    during a crime are between the ages of 25-31,
    drive a 4x4 truck, are white, and are highly
    intelligent
  • Therefore, the offender may be a white male, age
    25-31, who lives with his mother, and drives a
    4x4 truck.

62
Alternate View of Reasoning
  • Sloman (1996)
  • Two complementary systems of reasoning
  • Associative system
  • Rule-based system
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