1. Human Cognitive Processes: psyc 345 Ch. 13 Reasoning and Decision Making Takashi Yamauchi © Takashi Yamauchi (Dept. of Psychology, Texas A&M University)

2. (Q1) what mental strategy do people often employ when they make probabilistic reasoning? (Q2) what decision strategies do people commonly use when they make a choice? What factor influences our choice behavior above and beyond our own rational judgments?

3. Reasoning People start with information and come to conclusions that go beyond that information. –You are incredibly nice today. What’s going on?

4. Even understanding a joke requires some form of reasoning (or inference)

5. Deductive reasoning vs. inductive reasoning Deductive reasoning –When the information you have is correct, you can necessarily reach a conclusion. Inductive reasoning –You can arrive at conclusions about what is probably true.

6. Deductive reasoning –Obama is the president of the US. –Only natural-born citizens of the US can serve as a president of the United States. –Conclusion: Obama is a natural-born US citizen. –Arnold Schwarzenegger is not a natural-born US citizen. –Conclusion: Arnold S. cannot be a president of the US.

7. Syllogism Premises and categorical syllogisms Premise 1: All birds are animals. Premise 2: All animals eat food. Conclusion: All birds eat food.

8. Premise 1: All people in Texas love the Spurs. Conclusion: All Texans hate the Lakers. Is this true? Is this valid?

9. Premise 1: All Texans love the Spurs. Premise 2: All people who love the Spurs hate the Lakers. Conclusion: All Texans hate the Lakers. Is this valid? Is this true? –Logical validity: A syllogism is valid when its conclusion follows logically from its premises.

10. (Q1) what mental strategy do people often employ when they make probabilistic reasoning?

11. Watson four-card problem There is a letter on one side of each card and a number on the other side. Indicate the minimum number of cards you need to turn over to test the following rule: If there is a vowel on one side, then there is an even number on the other side.

12. Real-life concrete information helps your reasoning

13. Fig. 12-8, p. 447 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 the following rule: If a person is drinking beer, then he or she must be over 19 years old.

14. Answer The answers for the letter-number problem and the beer-age problem are identical. You have to turn E and 7 –Only 7 % of the participants were correct. You have to turn beer and 16 years old. –73 % of the participants were correct.

15. Why is there such a big difference in the two problems? People use a real-life schema to solve a reasoning problems.

16. Inductive Reasoning Conclusions do not definitely follow from premises. Conclusions are only probably true. E.g., –(premise) Many people in Texas love football. –(conclusion) Many people in Oklahoma like football.

17. Inductive reasoning Examples: Will the stock market go up or down next year ? Which movie will win the Oscar? Does she say “yes” if I ask her to go out? How likely am I accepted to a medical school? How much money can I make if I choose carrier A? Is this plan likely to succeed? Is this guy a good fit for this job?

18. Inductive reasoning People draw a conclusion based on “observations”. But when do they feel more / less certain about our conclusion? What are the better ways to persuade others?

19. (Q1) what mental strategy do people often employ when they make probabilistic reasoning? –By and large, people tend to use quick and easy heuristics. –Availability, representativeness,

20. Demo 1: Which is more prevalent, words that begin with the letter r, or words in which r is the third letter?

21. Demo 2: For each pair of cases, which cause of death you consider more likely for people in the US? Homicide Appendicitis Auto-train collisionDrowning Measles Smallpox Botulism Asthma Asthma Tornado AppendicitisPregnancy

22. Availability heuristics Demo 1: Which is more prevalent, words that begin with the letter r, or words in which r is the third letter? About 70% of the respondents tend to respond that there are more words with r in the first position than in the third position. (In reality, there are three times more words that have r in the 3 rd position).

23. Pairs of “causes of death” are listed below the graph, with the least likely cause on the left. The number in parentheses on the right indicates how many more times more people were actually killed by the cause on the right. The bars in the graph indicate the number of people who judged the least likely alternative in each pair as causing the most deaths.

24. Availability Heuristics 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. E.g., –Think of words that begin with r. –Think of words that have r in the third position? –Which is easier to think of?

25. 90% of success is just showing up. –Woody Allen http://blog.bplans.com/2008/02/22/90-of-success- is-just-showing-up/ http://en.wikiquote.org/wiki/Woody_Allen

26. Murder rate Finland vs. Dominica vs. Italy The murder rate of Finland is twice higher than that of Italy. The murder rates of Finland and Dominica are about the same. http://www.nationmaster.com/graph/cri_mur_perca p-crime-murders-per-capita

27. Crime rate El Paso vs. Colorado Springs vs. Denver vs. Boston –El Paso (4.57 / 1000) –Colorado Spring (4.9 / 1000) –Denver (5.78 / 1000) –Boston (9.92 / 1000) –http://en.wikipedia.org/wiki/United_States_citi es_by_crime_rate

28. Representative heuristics We tend to make judgments based on resemblance. –The probability that an event A comes from class B is determined by how well A resembles the properties of class B. –Is A likely to be B? –  we say yes, to the extent that A resembles B.

29. Representative heuristics Demo 1 We randomly pick one male from the population of the US. That male, Robert, wears glasses, speak quietly, and reads a lot. Is it more likely that Robert is a librarian or a farmer?

30. Representative heuristics The description of Robert as wearing glasses, speaking quietly, and reading a lot matched people’s image of a typical librarian.  people make a judgment based on how closely Robert resembles a typical “librarian” or a “farmer.”

31. Demo 2: Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in antinuclear demonstrations. Which of the following alternatives is more probable? 1. Linda is a bank teller. 2. Linda is a bank teller and is active in the feminist movement.

32. Many people choose 2, but 2 cannot be more likely than 1. Why? People used representative heuristics, and they are incorrectly assuming that the description of Linda fits an image of feminists.

33. (Q2) what decision strategies do people commonly use when they make a choice? What factor influences our choice behavior above and beyond our own rational judgments?

34. Decision making and choosing among alternatives

35. The utility approach to decisions Basic idea: –People make decisions in order to maximize the utility associated with the choice.

36. buying a car Honda Accord vs. Mercury Cougar You have $20,000 to spend.

37. Honda Accord Mercury Cougar

38. Compare the features of the two cars Accord is slightly more expensive than Cougar. Cougar has better horse power than Accord. Accord has better fuel economy. Cougar is more stylish than Accord. Expected utility theory you choose the one that gives you the maximum value (the maximum satisfaction you get). Sum(U(A))> Sum(U(B)) --> select A what is “valuable” is subjective.

39. Expected utility theory  mental arithmetic Choose Honda Accord if Sum(Accord) > Sum(Cougar)

40. $price willingness to buy / sell seller buyer Selling / Buying a car

41. McDonald Probability to say “Yes, go for it!!” girl boy Dating scene $ cost KFC Christopher’s Mr. G’s Square one Café Excel

42. Basic assumption in Economics –People’s choice behavior is driven to maximize their self-interest. Rational analysis Milton Friedman (2:24) http://www.youtube.com/watch?v=RWsx1X8PV_A But you see many irrational behaviors. –Dot-com bubble, housing bubble –Why do we make so many irrational decisions?

43. People may be rational, but their decision is very much influenced by many psychological factors (such as emotion, attention, and memory) Behavioral economics –Behavioral economics examines people’s economic choice behavior from a vantage point of cognitive psychology. Behavioral economics. 4:16 –http://www.youtube.com/watch?v=Fa-mIosWOK8 Interview: NPR Behavioral economics (9:00)

44. Amos Tversky (1937 – 1996)Daniel Kahneman (1934 –)

45. 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

46. Focusing illusion –People focus on one aspect of a situation and ignore other aspects. 1. How happy are you? 2. How many dates did you have last month? –Correlation = 0.12 1. How many dates did you have last month? 2. How happy are you? –Correlation = 0. 66

47. Your decisions depend on how choices are presented Demo Coglab Risky decisions

48. Imagine that the US is preparing for the outbreak of an unusual Asian 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?

49. Imagine that the US is preparing for the outbreak of an unusual Asian 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 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?

50. Fig. 12-15, p. 470

51. Risk-aversion strategy –The idea of saving 200 lives with certainty is more attractive than the risk that no one will be saved. Risk-taking strategy –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.

52. When a problem is framed in terms of gain, we tend to choose sure things (risk- aversion strategy). When a problem is framed in terms of loss, we tend to choose risky things (risk- taking strategy)

53. If you are lucky, you have a chance to win $1000. Which game do you choose? –Game A. a sure gain of $240 –Game B. 25% chance to gain $1000 and 75% chance to gain nothing –Game A  84% –Game B  1 6%

54. 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%

55. Imagine that the US is preparing for the outbreak of an unusual Asian 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.

56. an unusual Asian disease that is expected to kill 600 people. –Program A  200 people will be saved –Program B  1 / 3 probability  600 saved And 2 / 3 probability  no people will be saved. 400 die 200 saved 400 die

57. an unusual Asian disease that is expected to kill 600 people. –Program C  400 people will die. –Program D  1 / 3 probability nobody will die, and 2 / 3 probability  600 people will die. 400 die 200 saved

58. 400 die 200 saved 400 die 200 saved 400 die

59. If you are lucky, you have a chance to win $1000. Which game do you choose? –Game A. a sure gain of $240 Expected Utility = $240 –Game B. 25% chance to gain $1000 and 75% chance to gain nothing Expected Utility = $1000 * 0.25 + $0 * 0.75 = $250 –Game A  84% –Game B  1 6%

60. 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 Expected Utility = $1000- $750 = $250 –Game D. 75% chance to lose $1000 and 25% chance to lose nothing. Expected Utility = $1000 - $1000 * 0.75 - $0 * 0.25 = $250 –Game C.  13% –Game D.  87%