Human Cognitive Processes: psyc 345

Ch. 13 Reasoning and Decision

Making

Takashi Yamauchi© Takashi Yamauchi (Dept. of Psychology, Texas A&M University)

(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?

Reasoning

• People start with information and come to conclusions that go beyond that information.

– You are incredibly nice today. What’s going on?

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

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.

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.

Syllogism

• Premises and categorical syllogisms

• Premise 1: All birds are animals.

• Premise 2: All animals eat food.

• Conclusion: All birds eat food.

• Premise 1: All people in Texas love the Spurs.

• Conclusion: All Texans hate the Lakers.

• Is this true?

• Is this valid?

• 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.

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

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.

• Real-life concrete information helps your reasoning

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.

• 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.

Why is there such a big difference in the two problems?

People use a real-life schema to solve a reasoning problems.

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.

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?

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?

(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,

• Demo 1:

• Which is more prevalent, words that begin with the letter r, or words in which r is the third letter?

• Demo 2:For each pair of cases, which cause of death you

consider more likely for people in the US?

Homicide Appendicitis

Auto-train collision Drowning

Measles Smallpox

Botulism Asthma

Asthma Tornado

Appendicitis Pregnancy

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 3rd position).

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.

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?

• 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

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_percap-crime-murders-per-capita

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_cities_by_crime_rate

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.

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?

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.”

• 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.

• 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.

• (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?

Decision making and choosing among alternatives

The utility approach to decisions

• Basic idea:– People make decisions in order to maximize

the utility associated with the choice.

buying a car

• Honda Accord vs. Mercury Cougar

• You have $20,000 to spend.

• Honda Accord

Mercury Cougar

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.

• Expected utility theory

mental arithmetic

• Choose Honda Accord if

• Sum(Accord) > Sum(Cougar)

$price

willingness to buy / sell

seller

buyer

Selling / Buying a car

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Probability to say “Yes, go for it!!”

girl

boy

Dating scene

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• 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?

• 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)

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

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

• 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

Your decisions depend on how choices are presented

• Demo

• Coglab

• Risky decisions

• 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?

• 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?

Fig. 12-15, p. 470

• 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.

• 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)

• 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 16%

• 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%

• 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.

• 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

• 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 die200 saved200 saved

400 die200 saved200 saved

400 die

200 saved

400 die

• 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 16%

• 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%