Judgment Flashcards

1
Q

What was Tversky and Kahneman (1983) Linda problem?

A
  • Students given a statement which they had to rate what options were more probable
  • 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 anti-nuclear demonstrations.
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2
Q

What is The conjunction fallacy in the Linda problem?

A
  • 85% of undergraduates judged h (bank teller and feminist) to be more likely than f (bank teller)
  • But: h is of the form ‘Linda is both X and Y’ f is of the form ‘Linda is X
  • So: h must be less likely than f
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3
Q

What was argued about the Linda problem regarding to how many options there were?

A
  • Perhaps because there are so many options, people simply don’t notice the relationship between f and h?
  • Tversky & Kahneman (1983) gave 142 people a simplified version of the problem containing only the two options of interest (f & h).
  • Still, 85% made the conjunction fallacy
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4
Q

What was argued about the Linda problem regarding to the language?

A
  • Perhaps people interpret ‘Linda is bank teller’ to mean ‘Linda is a bank teller & not active in the feminist movement’?
  • In that case, their judgements could be correct
  • Tversky & Kahneman (1983) changed the statement to: ‘Linda is a bank teller whether or not she is active in the feminist movement’
  • 57% of people made the conjunction fallacy
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5
Q

What is Heuristics?

A

Quick procedures that frequently find the correct solution but are not guaranteed to do so (‘cognitive short-cuts’ and ‘rules of thumb’)

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6
Q

What are Algorithms?

A

Procedures that are guaranteed to find a solution if one exists, but may take a very long time

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7
Q

What is the Representativeness heuristic in the Linda problem?

A

-“Linda is a bank teller and is active in the feminist movement” is more representative of the ‘kind of person’ Linda seems to be.

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8
Q

What were the findings of the Linda problem?

A
  • Separate groups asked to rank the eight ‘Linda’ outcomes on either representativeness or on probability
  • Correlation of 0.99 between the mean rankings
  • Similar proportions in each group made the conjunction ‘fallacy’ (note this was not a fallacy for the representativeness group)
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9
Q

What task did Tversky and Kahneman (1983) do looking at the USA and the Soviet Union?

A
  • Participants in International Congress on Forecasting. Different groups evaluated the probability of statements a and b
  • a. A complete suspension of diplomatic relations between the USA and the Soviet Union, sometime in 1983
  • b. A Russian invasion of Poland, and a complete suspension of diplomatic relations between the USA and the Soviet Union, sometime in 1983
  • Probability estimates for b higher than for a
  • Different task
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10
Q

What did Tversky & Kahneman (1983) find looking at -ing words?

A
  • If you pick 2000 words at random from a novel, will there be more words ending ‘ing’ or more words ending ‘n’?
  • Most said ‘ing’ which must be wrong
  • Availability heuristics, more likely to bring it to mind
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11
Q

What happened in the task looking at words starting with ‘r’?

A
  • If you pick a word (over three letters long) at random from an English text, is it more likely that the word starts with an ‘r’ or has ‘r’ as its third letter?
  • Most participants said ‘starts with r’ was more likely. Actually, many more words have ‘r’ as their third letter, but these are harder to bring to mind.
  • Easier to generate words beginning with r, than ending with r
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12
Q

What is the Availability heuristic?

A

-The easier it is to bring an event to mind, the more likely that event is judged to be.

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13
Q

What did Lichtenstein et al (1978) find when looking at Asthma and tornados?

A
  • Asked participants to judge which was the most likely of two causes of death
  • For example, is it more likely that someone will die in a tornado or from asthma?
  • Identified “many, often severe, misconceptions”
  • 58% of student sample thought tornado was more likely (actually asthma is 20 times more likely)
  • May be due to availability, unlikely to hear stories of people struggling with asthma
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14
Q

What did Slovic et al (1982) find when looking at death?

A
  • Over estimation and under estimation of what cause death

- E.g. smallpox vaccinations vs motor vehicle accident

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15
Q

What did Coombs and Slovic (1979) find about death and media coverage?

A
  • Newspaper reports over-represented more ‘dramatic’ causes of death (disasters, accidents, homicide etc.)
  • People’s risk judgements were related to frequency of media coverage
  • More evidence for use of an availability heuristic
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16
Q

What did Young et al (2008) find when looking at diseases with high media presence?

A

Diseases with high media presence (e.g. avian flu) judged more severe than other diseases

17
Q

What did Clark and Teasale (1985) find when looking at mood?

A
  • Positive and negative memories recalled more in the appropriate mood (in patients with depression)
  • Therefore, words and associations change their availability
18
Q

What task showed end anchoring?

A
  • Tversky & Kahneman (1974)
  • Group 1: Is % of African countries in UN < > 10%? Now estimate number of countries (24%)
  • Group 2: Is % of African countries in UN < > 65%? Now estimate number of countries (45%)
  • Anchoring participants at either 10% or 65%
  • Group 1: estimate product of 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 (2,250)
  • Group 2: estimate product of 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 (512)
19
Q

What Range of heuristics are there?

A

– Representativeness
– Availability
– End anchoring

20
Q

What do mathematicians say about single events?

A
  • Some say that probabilities can never be assigned to single events
  • Others disagree
  • Is it fair to test people’s judgements against this norm?
  • Chase et al., 1998
21
Q

How did Cosmides and Tooby (1996) change Cascells medical study?

A

-Rephrased Cascells et al.’s (1978) medical diagnosis problem in terms of frequencies
– Input information changed from percentages to frequencies
– Question changed from single-event probability to frequency judgement

22
Q

What did Fiedler (1988) when looking at the frequency version of the Linda problem?

A
  • Frequency version of ‘Linda problem’
  • 100 women fit this description: – Single, outspoken, very bright. Studied philosophy at university, deeply concerned with social justice and an antinuclear protester
  • How many are bank cashiers?
  • How many are bank cashiers active in the feminist movement?
  • 77% correct
23
Q

Frequentist approach: Evaluation

A
  • Performance on some tasks improves when problems are phrased in terms of frequencies rather than single event probabilities
  • But might this simply make the calculations easier?
  • Also, other tasks are performed badly despite frequentist phrasing