Review

2. Review • We have Selective Perception • Context Dependent • Influenced by expectations • We try to reconcile disparate beliefs and actions • Our memory isn’t so good

3. Selective Perception • There are limits to how much we can perceive at once.

4. Selective Perception • We tend to see what we expect to see. Half the class close your eyes.

5. Selective Perception • We tend to see what we expect to see. There is a 50% chance that Chris is lying to you.

6. Selective Perception • We tend to see what we expect to see. Half the class close your eyes.

7. Story Time

8. Selective Perception • Survey Research! • 1 (not at all) - 10(totally cool) • How much did you like Chris’s story? • How accurate would you guess Chris’s story was?

9. Selective Perception • Expectations matter Practical Example

10. Context Dependence • We don’t perceive things independently. Context matters: • Distracting or complementary stimuli

11. Cognitive Dissonance

12. How we resolve Cognitive Dissonance • Reduce importance • Add more consonant beliefs • Change beliefs

13. Memory • Bias distorts • Diminishes • If memory diminishes, what are we using to make ad hoc decisions? • What do you think about Michael Jordan?

14. How Questions Affect Answers Section II

15. Order Effects First Response influences Second Response Statistics vs. This Class Order of Alternatives Matters Fewer, the same number, or more?

16. Pseudo-opinions How do you feel about the Cookies Act now that it has been passed in the United States Senate?

17. Filtering out Pseudo-opinions Unfiltered: Oreos are better than Chips Ahoy. Do you agree or disagree? Oreos are better than Chips Ahoy. Do you have an opinion about that? If so, do you agree or disagree?

18. Inconsistency: do Attitudes reflect Behavior?

19. “Measuring an attitude, opinion or preference is not so simple as asking a question.” -Scott Plous

20. Question Wording and Framing Forced Choice Small extreme, large extreme, or middle? Frames of Reference How Tall? vs. How Short?

21. Social Desirability If program A is adopted, 200 people will be saved. If program B is adopted, p = 1/3 all will be saved, p = 2/3 no one is saved. VS. If program C is adopted, 400 people will die. If program D is adopted, p = 1/3 nobody will die, p = 2/3 all will die.

22. Psychological Accounting Regis: You’ve now won $125,000. Would you like to take the money, or try for $500,000? Remember, if you get the next question wrong, you will go back to $32,000. Howie: Deal or no deal?

23. Models of Decision Making Section III

24. Normative Models of Decision Making

25. Expected Utility Theory Nicholas Bernoulli’s Six Principles of Rational Decision Makers: 1. Ordering Alternatives 2. Dominance 3. Cancellation 4. Transitivity 5. Continuity 6. Invariance

26. Paradoxes in Rationality • The Allais Paradox for Cancellation • Ellsberg’s Paradox for Cancellation • Tversky’s study of Intransivity • Lichtenstein and Slovic’s Preference Reversal

27. Are violations of the theory truly irrational? Should we base our experiments on the behavior of rational actors? OR Should we first attempt to create behavioral models from observation?

28. Descriptive Models of Decision Making

29. Satisficing People don’t optimize when they make decisions. They choose paths that ------ satisfy their most important needs.

30. Prospect Theory Value rather than “utility” *Utility = Net Wealth *Value = Gains and Losses Preferences will depend upon how a problem is framed.

31. The Certainty and Pseudocertainty Effects • People pay more to remove 1 of 1 bullets than to remove 1 of 4 bullets. • Buy three get one free = 25% price reduction

32. Regret Theory • Based on Counterfactual Reasoning • 1. People feel rejoicing and regret • 2. People anticipate these sensations when they make decisions • Of course, when the decision may result in death, regret theory does not apply.

33. Multi-attribute Choice Compensatory Strategies • Linear Modeling • Weigh the dimensions by importance • Additive Difference • Weigh the differences among alternatives • Ideal Point Modeling • What does the ideal look like?

34. Noncompensatory Strategies • Conjunctive Rule • Eliminate alternatives • Disjunctive Rule • Alternatives evaluated on best attributes • Lexicographic Strategy • Choose a dimension to evaluate • Elimination-by-aspects • Choose a dimension to evaluate based on the probability of its importance

35. Expected Utility Theory vs. Prospect Theory Why must we consider both theories? What is more important, making people into rational decision makers, OR Allowing for the irrationality of their decisions?

36. Heuristics and Biases Chp. 10 – chp. 13

37. Overview • Representativeness Heuristic • The Availability Heuristic • Probability and Risk

38. Representativeness Heuristic • People often use “Heuristic” or general rules of thumb, to arrive at their judgment. Tversky and Kahneman— “People often judge probabilities …by the degree to which A resembles B”.

39. The Law of Small Numbers • “...a belief that random samples of a population will resemble each other and the population more closely than statistical sampling theory would predict.” • Examples: • Gambler’s fallacy – “the belief that a successful outcome is due after a run of bad luck…” • Examples: • The Hot Hand – “…a streak shooter in basketball or an athlete on a roll…” Remember that chance is not self-correcting!

40. Neglecting Base Rates • When people are provided with the descriptive information, they often ignore the base rates • Examples: • Among 100 persons, there are 30 engineers, and the other 70 are lawyers. Q: John is a 30-year old man. He is married with no children. A man of high ability and high motivation, he promises to be quite successful in his field. He is well liked by his colleagues. What is the probability that John is an engineer? Subjects give 50% Whenever possible, pay attention to base rates, do not be trapped with the detail description

41. Overview • Representativeness Heuristic • The Availability Heuristic • Probability and Risk

42. Availability Heuristic Tversky and Kahneman— “…Assess the frequency of a class or the probability of an event by the ease with which instances or occurrences can be brought to mind.” Example: Which is a more likely cause of death in the U.S. last year— stomach cancer or car accident? The Author notes that— “Some events are more available than others notbecause they tend to occur frequently or with high probability, but because they are inherently easier to think about, because they have taken place recently.” Do not trust your immediate intuitions for judgments of frequency or probability

43. Vividness • Decision makers are affected more strongly by vivid information than by pallid, abstract, or statistical information. • Because vivid information is more “available” and easier to recall than pallid information, it often has a disproportionate influence on judgments.

44. Imaginative Study • An imaginative event will increase its availability and make it appear more likely • Who will win?

45. Overview • Representativeness Heuristic • The Availability Heuristic • Probability and Risk

46. Bias of Probability and risk • Positive outcomes are viewed as more probable than negative outcomes • What was your dream when you were a child?

47. Bias of Probability and risk • Perceptions of risk are highly subjective.

48. Importance in research (From 2003) • Use heuristics and probability measures carefully • Apply corrective measures to your data to “undo” the effect of biases • Don’t let your “desire” for accuracy sway you towards inaccurate data

49. The Psychology of Judgment and Decision Making Chapter 13 to Chapter 16 By Sean

50. US$ 119,900 US$ 129,900 What do you think? US$ 139,900 US$ 149,900