S2W4Judg Flashcards

1
Q

Judgement

A

Deciding the likelihood of various events using incomplete information (likelihood rather than choice).

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2
Q

Inductive Reasoning

A

Making a conclusion that is probably, but not definitely, true:

All of the swans I have seen are white

I expect that all swans are white

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3
Q

Factors contributing to strength of an inductive argument

A

Representativeness of observations:
o How well do observations of category represent all members of it

Number of observations

Quality of the evidence

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4
Q

Availability Heuristic

A

Events that are more easily remembered are judged to be more probable than events that are less easily remembered.

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5
Q

Availability Heuristic

Tversky & Kahneman (1973)

A

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

70% said more words begin with r

In reality 3x more words have r in the third position

Easier to think of words that start with r than words with r as third letter

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6
Q

Availability Heuristic

Lichtenstein et al (1978)

A

Participants asked to judge prevalence of causes of death

Given pairs of causes of death and asked to say which was more prevalent

Appendicitis twice as fatal as pregnancy but pregnancy receives more media attention so people got a lot of pairs wrong.

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7
Q

Affect Heurist

A

Basing a judgement on how much dread one feels (if you’re scared you think it’s more likely to happen).

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8
Q

Illusory Correlation

A

You believe a correlation is present between two events, but this is false or weaker than assumed.

May be a stereotypes:

Oversimplified generalisation about group
(often negative)

Every time you see someone doing something negative it reinforces your stereotype even though it’s the minority.

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9
Q

Representativeness Heuristic

A

The probability that A is a member of class B.

Determined by how well properties of A resemble properties usually associated with class B.

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10
Q

Representativeness Heuristic

Kahneman and Tversky, (1974)

A

Randomly pick one male from population.

Robert, wears glasses, speaks quietly, and reads a lot. Is it more likely that Robert is a librarian or a farmer?

Most people guess librarian

Far more farmers than librarians in population

Ten times more male farmers than librarians (base rate information)

When only base rate is available, people will use this information

When descriptive information is available, people disregard base rate information, causing errors.

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11
Q

Conjunction Rule

A

Probability of two events cannot be higher than the probability of the single constituents.

Which of the following is more probable?

Linda is a bank teller

Linda is a bank teller and a feminist.

85% chose 2

Participants influenced by repetitiveness heuristic

Ignored the conjunction rule

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12
Q

Law of Large Numbers

A

The larger the number of individuals randomly drawn from a population, the more representative the resulting group will be of the entire population.

The larger the sample the more representative it is of the population.

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13
Q

Law of Large Numbers

Tversky and Kahneman (1974)

A

In the large hospital 45 babies are born each day.

In the small one 15 babies are born each day.

Although the overall proportion of genders is 50/50

Which hospital will have more days where 60%+ were girls?

  1. the large
  2. the small
  3. the same

22% picked small
22% picked large
56% picked same

Correct answer: the small hospital

Smaller samples of numbers of individuals less likely to be representative of general population.

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14
Q

Myside Bias

A

Tendency for people to evaluate evidence and test hypotheses in a way that is biased toward own opinions

Errors occur when people let their own opinions and attitudes influence how they evaluate evidence needed to make decisions.

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15
Q

Myside Bias

Lord et al. (1979)

A

Gave questionnaire to two groups, one in favour of capital punishment and one against.

Presented them with descriptions of research studies into capital punishment.

Participants rated articles – responses reflected attitudes they had at the start of the study.

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16
Q

Confirmation Bias

A

Tendency to selectively look for information that conforms to our hypothesis and overlook information that argues against it.

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17
Q

Confirmation Bias

Wason (1960)

A

2, 4 & 6 conform to a rule.

Write down sets of numbers and reasons for your choice to discover my rule.

I shall tell you whether your numbers conform to the rule or not and then you can tell me the rule.

Most common hypothesis was increasing intervals of two

Actual rule was three numbers in increasing order of magnitude.

Secret is to find sequences that don’t satisfy your rule but do satisfy Wason’s.

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18
Q

Decision Making

Utility Approach

A

People make a decision resulting in the maximum expected utility (money).

Influenced by Expected Utility Theory

People ignore optimum way of responding e.g. carry on gambling.

19
Q

Evaluation of utility approach

A

Advantages:

Specific procedures to determine the “best choice”

Problems:

People aren’t always motivated by money

Many decisions do not maximize the probability of the best outcome

20
Q

Denes-Raj and Epstein’s (1994) utility approach

A

Participants received money if they picked a red bean.

Gave participants a choice between picking from a bowl with 1 red and 9 white beans OR a bowl with 7 red beans and 93 white ones.

Many participants chose less-optimal bowl with more beans.

Participants explained that they knew probabilities against them, but felt they had a better chance as more red beans.

21
Q

Expected emotions

Kermer et al. (2006)

A

Compared people’s expected emotions with their actual emotions

Given $5 and told they would gain an additional $5 or lose $3 after a coin flip

Participants predicted how their happiness would change if they won or lost

People overestimated the negative effect of losing.

People only slightly overestimated the positive effect of wining.

People forget about coping mechanisms; leads to inefficient decision making.

22
Q

Incidental emotions

A

Emotions that are not specifically related to decision-making (may be related to personality, recent experience, or environment).

23
Q

Incidental emotions

Lerner et al. (2004)

A

Participants watched one of three film clips and asked to write how they would feel::

A person dying (sadness)
A dirty toilet (disgust)
Fish (neutral)

Then asked to determine price to sell or to buy items.

Those in S or D group willing to sell for less

Those in S group willing to pay more

D = need to expel things

S = need for change

24
Q

Context

Redelmeier and Sahafir (1995)

A

Found that adding alternatives to be considered can influence decisions.

Given a patient that was experiencing the same symptoms for each condition:

Should doctor prescribe medication A?
o 72% opted yes

Should doctor prescribe medication A or B?
o 47% opted neither

Faced with more difficult decision lead to making no decision.

25
Q

Choice Presentation

A

Decisions depend on how choices are presented.

26
Q

Choice Presentation

Johnson & Goldstein (2003)

A

Opt-in/Opt-out procedure for organ donation:
Countries with opt-in procedure: low consent rate (people don’t bother applying)

Countries with opt-out procedure: high consent rate (people don’t bother changing)

Status quo bias: the tendency to do nothing when faced with making a decision.

27
Q

Framing effect

Tversky and Kahnemann (1981)

A

Decisions are influenced by how a decision is stated.

Two alternative programs to combat a disease:

A: 200 people saved.

B: 1/3 probability that 600 people will be saved, 2/3 probability that no one will be saved.

C: 400 people will die.

D: 1/3 probability that nobody will die, 2/3 probability that 600 people will die.

A and B are the same as C and D but are worded in terms of life not death.

When situations are framed in terms of gains, people tend toward a risk-aversion strategy.

When situations are framed in terms of losses, people tend toward a risk-taking strategy.

28
Q

Neuroeconomics

A

Investigates how brain activation is related to decisions involving gains or losses.

Areas of brain identified as people make decisions playing economic games.

Decisions influenced by emotions, and emotions are associated with activity in specific areas.

29
Q

Sanfey et al. (2003) Neuroeconomics

A

Two players: one proposer, one responder.

Proposer given money; makes offer to responder as to how money is split.

If responder accepts, both get money; if rejects, neither get anything.

Utility theory predicts responder should always accept.

20 games:
• 10 with humans
• 10 with computer

Rejected unfair offers from human but not computer.

Less angry with computer

30
Q

Sanfey et al. (2003) economics brain activity

A

Right anterior insula (emotional states) activated 3x more when participants rejected offers.

Participants with higher activation to unfair offers rejected more.

Prefrontal cortex (complex cognitive behaviours) also activated, but same for all conditions.

Suggests that:

Emotional goal of resenting unfairness handled by anterior insula

Cognitive goal of accumulating money handled by prefrontal cortex

31
Q

Reasoning

A

The process of drawing conclusions.

32
Q

Deductive Reasoning

A

Drawing conclusions that are definitely valid provided the assumptions are true.

Based on formal logic but most people don’t use formal logic to solve them.

Based on observation

33
Q

Syllogisms

A

Determining whether a conclusion logically follows from premises (statements).

Basic form of deductive reasoning:

Two statements called premises

Third statement called conclusion

34
Q

Categorical syllogisms

A

Premises and conclusion all begin with all, no, or some

35
Q

Categorical syllogisms validity

A

Syllogism valid when form of syllogism follows logically from its two premises

Does not necessarily mean that the conclusion is true

If two premises of a valid syllogism are true, then the syllogism’s conclusion must be true

36
Q

Categorical syllogisms belief bias

A

Tendency to think syllogism is valid if its conclusion is believable

Evan et al. (1983): invalid syllogisms with believable conclusions were judged as valid 71% of the time

37
Q

Mental models

A

Specific situation represented in a person’s mind that can be used to determine validity of syllogisms in deductive reasoning.

Create an iconic model of a situation

Generate tentative conclusions about model

Look for exceptions to falsify model

Determine validity of syllogism

38
Q

Conditional Syllogisms

A

If I study I’ll get a good grade.
I studied.
Therefore I’ll get a good grade.

vs.

If I study I’ll get a good grade.
I got a good grade.
Therefore I studied.

39
Q

4 syllogisms with same first premise

A

P therefore Q (true 97% got correct)

Not Q therefore not P (true 60% got correct)

Q therefore not P (false: 40% got right)

Not P therefore not Q (false 40% got right)

40
Q

Conditional reasoning

Wason (1966) Four-Card Problem

A

Each card has letter on one side and number on other

Rule applies to all cards

Select only cards that need to be turned over to decide whether or not the rule is correct

Results:

First card chosen:
o 53% turned over first card

Second card chosen:

o 46% turned over third card (does not test rule)

o 4% turned over fourth card (does test rule – correct)

41
Q

Falsification principle

A

To test a rule, it is necessary to look for situations that would falsify the rule

42
Q

Griggs and Cox (1982) falsification principle

A

Stated problem in real-world terms:

If a person is drinking beer, then he must be over 18

73% correct: Flip over beer & 16 years old (can test the rule)

People familiar with regulations

43
Q

Permission schema

A

“if you are 18, then you are allowed to drink beer” – people fill in the gaps with existing knowledge.

44
Q

Cheng and Holyoak (1985) permission schema

A

Tested for the involvement of permission schema in reasoning:

You are an immigration officer at the airport. Among the documents you have to check is a sheet.

It indicates (a list of tropical diseases) (inoculations travelers have received).

You have to make sure that if the form says ‘entering’ on one side, then the other side includes cholera among the list of diseases (to ensure protection).

This is to ensure that entering passengers are protected against the disease.

Which would you have to turn over?

List of diseases condition: 62% correct

Inoculation condition: 91% chose correct cards