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. Howard’s 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 6’7”, 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. Steve’s description fits our vision of a librarian, Linda seems to be more of a feminist

17. Representativeness Heuristic • Gambler’s 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 1970’s &1980’s 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 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 slide—are 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 again…Predict your past answer 1 means you were sure it was true 10 means you were sure it was false

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 • 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. A 2 X 3

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 doesn’t matter • Rule does not state that all even numbers have to have vowels • X card doesn’t 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) • 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. Beer 22 Coke 17

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 female Some men are female All men are animals Some animals are aggressive Some men are aggressive  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