Flashcards in Heuristics and biases: prospect theory Deck (62):

1

## What is prospect theory?

### A descriptive theory of decision making.

2

## What did Kahneman and Tversky document?

### Numerous deviations from normative decision making.

3

## How did Kahneman and Tversky explain deviations from normative decision making?

### People often rely on heuristics to make decisions, which create systematic biases.

4

## What did the research programme resulting from Kahneman and Tversky's claims become known as?

### Heuristics and biases.

5

## What is the representativeness heuristic?

### Most people believe that two things are likely to occur than one, which can't be true according to probabilities (the conjunction fallacy).

6

## Give two examples of the representativeness heuristic.

###
1. Nuclear war, vs. nuclear war triggered by a third country.

2. Linda - bank teller or bank teller and active in the feminist movement.

7

## What is the conjunction fallacy?

### The conjunction or co-occurrence of two events cannot be more likely than the probability of either event alone.

8

## What did Tversky & Kahneman (1982) state about the conjunction fallacy?

###
- The fallacy occurs because specific scenarios appear more likely than general ones

- This is because they appear more representative than they really are

- “As the amount of detail in a scenario increases, its probability can only decrease steadily, but its representativeness and hence its apparent likelihood may increase” (p.98)

9

## Give an example where people incorrectly use 'the law of small numbers'.

###
The mean IQ of the population of 8th graders is known to be 100, what's the mean IQ in a sample of 50 pupils where the first child tested has an IQ of 150?

Most people incorrectly answer 100, whereas if the first IQ is 150 and the rest have a mean of 100 = total of 5050 = average IQ of 101.

10

## What did Tversky & Kahneman (1971) state about people's use of the law of small numbers?

### That people who respond 100 assume there would be some low IQs to balance out the high ones - they believe that chance is self-correcting, whereas the law of small numbers is non-existent.

11

## What is the 'law of small numbers'?

### The false idea that random samples of a population will resemble each other more closely than statistical sampling theory would predict.

12

## What is the law of large numbers?

### The larger the sample you draw from a population, the closer its average will be to the population average.

13

## What is local representativeness (Kahneman and Tversky, 1972)?

### An example of the law of small numbers - when people are asked to write down random sequences of numbers/letters/coin tosses, they tend to try to make the sequence look random at every point

14

## What gives rise to the gamblers fallacy?

### The representativeness heuristic, through the law of small numbers.

15

## What is the gamblers fallacy?

### The that a series of independent trials with the same outcome will be followed by an opposite outcome sooner than is expected by chance, for example when given the sequence "tails, heads, tails, heads, heads, heads, heads…" most people think tails follows.

16

## What is the 'hot hand'?

### People's perceptions of lucky streaks in games.

17

## What did Gillovich, Vallone & Tversky (1985) do?

### They examined people's perceptions of the hot hand in basketball, reporting statistical analyses of lucky streaks.

18

## What did Gillovich, Vallone & Tversky (1985) find?

### 'Lucky streaks' were simply misconceptions - successful shots during lucky streaks are actually no more likely than that player's overall probability of a lucky streak... Lucky streaks are an illusion.7

19

## What do judgements of Xs and Os show about the 'hot hand'?

### When the probability of alternation was set at .4, .5, .6, .7, .8 or .9, subjects thought that the higher probability of alternation sequences are more likely to be chance, when in fact the opposite is true.

20

## What is the availability heuristic?

### The bias towards options that we have more information about.

21

## Give an example of the availability heuristic.

### Most believe you’re more likely to die on a plane than by being kicked by a donkey, whereas the latter is true; in short it's a memory effect affected by media coverage etc.

22

## What do decision makers do when using the availability heuristic, according to Tversky & Kahneman, (1974)?

### “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”

23

## What did Tversky & Kahneman (1973) do?

### Asked subjects if there were more words with K as the 3rd or 1st letter in English.

24

## What did Tversky & Kahneman (1973) find?

### 69% of people answered incorrectly: there are twice as many words with K as the 3rd letter than the 1st.

25

## How did Tversky & Kahneman (1973) explain their results?

### They argued that because our lexicon is organised by spelling (or at least phonetics) more words beginning with K are available for retrieval.

26

## What is availability influenced by, other than memory?

### Imagination.

27

## What did Caroll (1978) reason?

### If easily imagined events are judged to be more probable than the very act of imagination might increase availability and consequently judgements of probability.

28

## What is an example of the availability heuristic being improved by imagination?

### Participants, a day before the 1976 presidential election, were asked to imagine one of two scenarios involving either candidate winning, and when asked who they thought would win their beliefs were consistent with the imagined scenario.

29

## What heuristic is hindsight bias part of?

### The availability heuristic.

30

## What is hindsight bias?

### The tendency to view what has already happened as inevitable and obvious without realising that retrospective knowledge the outcome is influencing one's judgement.

31

## What did Fischoff (1975) do?

### Had participants read true historical accounts of incidents which they were unfamiliar with e.g. the battle between the British and Nepalese Ghurkhas in 1814. Half were told the outcome, they then had to assign probabilities to outcomes

32

## What did Fischoff (1975) find?

### Participants who were told the outcome gave higher probability to the actual outcome than those who were uninformed.

33

## What did Fischoff and Beyth (1975) do?

###
Asked Israeli participants to estimate the probability of 15 different outcomes of Nixon's (1972) trips to China and the USSR before they took place.

2 weeks - 6 months after the trips participants had to recall their original ratings and indicate if the event occurred.

34

## What did Fischoff and Beyth (1975) find?

### 75% of participants remembered assigned higher probabilities than they had to events they thought had occurred.

35

## What are Kahneman and Tversky's three heuristics?

### The representativeness heuristic, the availability heuristic and anchoring and adjustment.

36

## What is anchoring and adjustment?

### The heuristic where numerical estimates (e.g. probabilities) are formed by taking an initial value (an anchor) and adjusting it.

37

## How did Tversky & Kahneman (1974) demonstrate anchoring and adjustment?

### They asked high school students to estimate answers to 1x2x3x4x5x6x7x8 and 8x7x6x5x4x3x2x1 within 5secs, and found that mean estimates were 512 and 2250 respectively but the answer is 40,320; the anchor was determined by left to right calculation.

38

## What did Tversky & Kahneman (1974) state about anchors?

### The anchor “may be suggested by the formulation of the problem, or it may be the result of a partial computation”

39

## What did Tversky & Kahneman (1974) do with random number generation?

### Produced a number 0-100, then asked participants to estimate the percentage of African countries in the UN and indicate whether the estimate was greater or less than the random number.

40

## What did Tversky & Kahneman (1974) find with random number generation?

### Participants given high random numbers produced higher estimates than those given low numbers. Modifications of the estimate are always too small because of the anchor effect.

41

## Who first described the Asian disease problem?

### Tversky & Kahneman, 1981.

42

## What is the Asian disease problem?

### Imagine the UK is preparing for the outbreak of an unusual Asian disease which is expected to kill 60,000 people. Two programs have been proposed.

43

## What are the two proposed programs for the Asian disease problem?

###
Program A: 20,000 will be saved OR Program C: 40,000 will die

Program B: 1/3 chance 60,000 will be saved but a 2/3 chance that no one will be saved OR Program D: 1/3 chance no one will die but a 2/3 chance that 60,000 will die

44

## What did Tversky and Kahneman (1981) find with the Asian disease problem?

### The framing of the question reverses the decisions participants make - people are risk averse for gains (lives seen as gains), so 70% choose A over B, but risk seeking for losses (loss aversion), so 20% choose C over D.

45

## What is another example of how framing of questions affects their answers?

### Rugg (1941) - asked US citizens if public speeches against democracy should be either allowed or forbidden. 62% said no to the allowed question, but only 46% said yes to the forbid question.

46

## Give examples of deviations from rational choice theory that prospect theory aimed to explain.

### The Allais paradox, Ellseberg paradox and the framing effect.

47

## What are the two main components of prospect theory?

### Utility and probability.

48

## Describe the value function proposed by Tversky and Kahneman in 1981.

### Where the x-axis is gains and losses and the y axis utility, functions for gains and losses are asymmetric. Utility is larger for losses than gains.

49

## What choices demonstrate the value function (being risk averse for gains and risk seeking for losses)?

###
Choice 1: A) Sure gain of £240 or B) 25% of £100, 75% of nothing

- People choose A

Choice 2: C) Sure loss of £750 or D) 75% of £1000, 25% of nothing

- People choose D

However analysis shows it's better to choose B and C over A and D (Tversky and Kahneman, 1981).

50

## What is the π function?

### The certainty effect - we don't treat probabilities as they're stated, the pi function distorts them (objective p -> subjective π).

51

## Give an example of the π function in action.

### Given a choice between p(1)£30 or p(0.8)£45, most people select A despite B having a higher EV. However given a choice between p(0.2)£45 or p(0.25)£30, most people choose A which this time does have a higher EV.

52

## How are subjective probabilities < 1.0 are weighted relative to objective probabilities?

### They're underweighted.

53

## What is explained by the certainty effect (π function)?

### The Allais paradox and Zeckhauser problem (subjects tend to pay more to remove the only bullet from a gun in Russian roulette than to remove one out of 4).

54

## What did Kahneman & Tversky (1979) do to demonstrate the π function?

### Asked participants to suppose they were evaluating insurance policies against theft or damage to properties and to weight premiums against benefits, then to consider a policy in which the premiums were halved but only paid out in 50% of claims.

55

## What did Kahneman & Tversky (1979) find about the π function?

### 80% of participants wouldn’t buy the probabilistic insurance, therefore halving the probability of a loss is less valuable than reducing the probability from half to 0. I.e. we prefer to eliminate risk than to reduce it.

56

## What is a consequence of the pi function for very low probabilities?

### Each additional unit is over-weighted, e.g. people tend to believe that their chances of winning the lottery are larger than they actually are.

57

## What is a consequence of the pi function for very large probabilities?

### Additional units are under-weighted, as shown by Lichtenstein et al. (1978), who compared participants' estimated frequencies of deaths as a function of actual frequencies. They estimated less than is true for low frequency e.g. botulism and more than is true for high frequency e.g. cancer.

58

## Give evidence that some people are more confident than others despite being 'experts' in their field.

###
Comparison of confidence and actual probability of:

a) weather forecasters' predictions of precipitation

b) doctors' diagnoses of pneumonia

Shows that doctors show substantial overconfidence.

59

## What have studies on confidence using Superpowers A and B situations related to the cold war found?

### People couldn't distinguish between the military actions of the USA and USSR, and confidence was unrelated to accuracy - even high confidence responders couldn’t discriminate above chance.

60

## What is a limitation of prospect theory?

### It doesn't give any psychological reasons for the shapes of functions - neither RCT nor prospect theory consider alternative outcomes.

61

## According to regret theory, what do we do?

### Compare outcomes, particularly after the fact, so we regret a decision if an alternative outcome would have led to a higher payoff, even when the prospect was better. We also rejoice if our choice let to a better outcome than other alternatives. I.e. when we make a decision we also consider the emotional outcomes.

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