Reasoning and Decision-Making

Question 1

Probability judgments often deviate from the dictates of probability theory

What are the 2 theories?

Answer 1

1) Heuristics and the biases
2) Ecological rationality

Question 2

Apparent biases may be rational responses given the ecology of the human decision-maker

This is known as…?

Answer 2

Ecological rationality

Question 3

Simplifying strategies that reduce effort but are prone to bias/error

This is known as…?

Answer 3

Heuristics and the biases

Question 4

Are people generally good or bad at working with probability?

Answer 4

Bad

Question 5

Define Heuristics and Biases

Answer 5

When people base their intuitive probability and frequency judgments on simple, experience-based strategies (“heuristics”) which are right (or good enough) most of the time

But which will sometimes lead to biased or illogical responses

Question 6

When people base their intuitive probability and frequency judgments on simple, experience-based strategies (“heuristics”) which are right (or good enough) most of the time

But which will sometimes lead to biased or illogical responses

This is known as…?

Answer 6

Heuristics and Biases

Question 7

What are the 3 types of Heuristics and Biases?

Answer 7

1) Availability
2) Representativeness
3) Anchoring

Question 8

1) Availability
2) Representativeness
3) Anchoring

Are these part of Ecological rationality or Heuristics and Biases?

Answer 8

Heuristics and Biases

Question 9

What view falls within a broader view of cognition that posits two systems:

1) A fast, associative, automatic, “System 1”

2) A slower, deliberative “System 2” that uses sequential processing and rule-based operations.

Answer 9

Heuristics and Biases

Question 10

Heuristics and biases falls within a broader view of cognition that posits two systems

What are they?

Answer 10

1) A fast, associative, automatic, “System 1”

2) A slower, deliberative “System 2” that uses sequential processing and rule-based operations.

Question 11

Describe the Availability Heuristic

Answer 11

Judgments are based on the ease with which relevant instances come to mind

Simply = If an event happens a lot then it will be easy to think of many past instances, so basing judgments on availability is sensible.

Question 12

Judgments are based on the ease with which relevant instances come to mind

Simply = If an event happens a lot then it will be easy to think of many past instances, so basing judgments on availability is sensible.

This is known as…?

a. Availability
b. Representativeness
c. Anchoring

Answer 12

a. Availability

Question 13

Overestimating the chances that a shark will attack you when you swim in the ocean is an example of…?

a. Availability
b. Representativeness
c. Anchoring

Answer 13

a. Availability

Question 14

When it is easier to bring to mind things that happen frequently

This is known as…?

a. Availability
b. Representativeness
c. Anchoring

Answer 14

a. Availability

Question 15

What are the 2 ways availability heuristic can entail bias?

Answer 15

1. Our experience of past events does not reflect their true frequencies
2. Events are easy to recall for some reason other than their frequency of occurrence

Question 16

1. Our experience of past events does not reflect their true frequencies
2. Events are easy to recall for some reason other than their frequency of occurrence

These are implications of…?

a. Availability
b. Representativeness
c. Anchoring

Answer 16

a. Availability

Question 17

Describe the study by Lichtenstein et al. (1978) in estimating causes of death

List 2 points

Answer 17

1) Ps estimate the number of US deaths per year due to 40 causes

2) The causes ranged from very rare (e.g., botulism, with one death per 100 million people) to very common (e.g., stroke: 102 000 deaths per 100 million people)

Question 18

Describe the results of the study by Lichtenstein et al. (1978) in estimating causes of death

Answer 18

Ps over-estimated rare causes and underestimated common causes

Question 19

Ps over-estimated rare causes and underestimated common causes of death

Why does this occur?

Answer 19

Because rare events/causes of death gets a lot of attention in media

But common events/causes of death happen too frequently that often, the media does not cover them because it would be too repetitive

Question 20

Describe the study by Tversky & Kahneman (1973) on the effect of memory

List 3 points

Answer 20

1) Ps listened to list of 39 names including:

19 famous women and 20 less famous men

OR

19 famous men
20 less famous women

2) Some Ps had to write down as many names as they could recall

3) Others were asked whether the list contained more names of men or of women

Question 21

Describe the results of the study by Tversky & Kahneman (1973) on the effect of memory

List 2 points

Answer 21

1) In the recall task, Ps retrieved more of the famous names (12.3 out of 19) than the non-famous names (8.4 out of 20). That is, famous names were more available.

2) 80 out of 99 (81%) Ps judged the gender category that contained more famous
names to be more frequent.

(e.g., the people given a list of 19 famous men and 20 less famous women reported that there were more men than women in the list)

Question 22

1) In the recall task, Ps retrieved more of the famous names (12.3 out of 19) than the non-famous names (8.4 out of 20). That is, famous names were more available.

2) 80 out of 99 (81%) Ps judged the gender category that contained more famous
names to be more frequent.

(e.g., the people given a list of 19 famous men and 20 less famous women reported that there were more men than women in the list)

What do these results suggest?

List 2 points

Answer 22

1) It seems that people made their proportion estimates by assessing the ease with which examples of each come to mind

2) When one category was easier to retrieve (via the fame manipulation) it was judged more frequent, even when it was actually experienced less often

Question 23

When one category was easier to retrieve (via the fame manipulation) it was judged more frequent, even when it was actually experienced less often

This is an example of…?

a. Availability
b. Representativeness
c. Anchoring

Answer 23

a. Availability

Question 24

When people mistakenly believe that two events happening together is more likely than one of the events happening alone

This is known as…?

Answer 24

Conjunction fallacy

Question 25

When subjective probability estimates sometimes violate this principle: The probability of event “A” cannot be less than
the probability of the conjunction “A and B”.

This is known as…?

Answer 25

Conjunction fallacy

Question 26

Describe Tversky and Kahneman’s (1983) study on conjunction fallacy

List 2 points

Answer 26

1) Ps were asked; In four pages of a novel (about 2,000 words), how many words would you expect to find that have the form:

a. seven letter words that end with ING

b. seven letter words with ‘n’ as the penultimate letter

2) All ING words have N as the penultimate letter, so the number of N words must be at least as large as the number of ING words.

Question 27

Describe the results of Tversky and Kahneman’s (1983) study on conjunction fallacy

List 2 points

Answer 27

1) Ps estimated, on average, 13.4 ending in ING words

2) But Ps only estimated 4.7 words with N as the penultimate letter

Question 28

1) Ps estimated, on average, 13.4 ending in ING words

2) But Ps only estimated 4.7 words with N as the penultimate letter

What do these results suggest?

List 2 points

Answer 28

1) People may be basing their judgments on the mental availability of relevant instances

2) It is easy to think of “ing” words (e.g., by thinking of words that rhyme) but we are less accustomed to retrieving words based on their penultimate letter, so N words are harder to retrieve and thus seem rarer.

Question 29

Under what circumstance will the conjunction fallacy problem disappear?

Answer 29

If/when participants apply a more systematic mental search strategy

Question 30

Define the representativeness heuristic

Answer 30

Judgments are based on the extent to which an outcome (or item) is representative of the process or category in question

Simply = Judgments of probability are based on assessments of
similarity

Question 31

Judgments are based on the extent to which an outcome (or item) is representative of the process or category in question

Simply = Judgments of probability are based on assessments of
similarity

This is known as…?

Answer 31

The representativeness heuristic

Question 32

According to the representativeness heuristic, when estimating a probability – for example, how likely it is that a person belongs to a particular category or the probability that an observed sample was drawn from a particular population

What do people assess?

Answer 32

The similarity between the outcome and the category (or between the sample and the population)

Question 33

When estimating a probability – for example, how likely it is that a person belongs to a particular category or the probability that an observed sample was drawn from a particular population – people assess the similarity between the outcome and the category (or between the sample and the population)

This is known as…?

a. Availability
b. Representativeness
c. Anchoring

Answer 33

b. Representativeness

Question 34

Judgments of probability are based on assessments of similarity

This is known as…?

a. Availability
b. Representativeness
c. Anchoring

Answer 34

b. Representativeness

Question 35

“an assessment of the degree of correspondence between a sample and a population, an instance and a category, an act and an actor or, more generally, between an outcome and a model.” (Tversky & Kahneman, 1983, p. 295).

This applies to…?

a. Availability
b. Representativeness
c. Anchoring

Answer 35

b. Representativeness

Question 36

Suppose that you meet a new person at a party and try to estimate the probability that they have tried internet dating.

The idea is that you base your judgment on the similarity between the person and your stereotype of internet-daters – that is, on the extent to which the person is representative
of the category “people who have tried internet dating”

This is an example of…?

a. Availability
b. Representativeness
c. Anchoring

Answer 36

b. Representativeness

Question 37

Describe Kahneman and Tversky’s (1973) study on base rate neglect

List 5 points

Answer 37

1) Ps were told that a panel of psychologists had interviewed a number of engineers and lawyers and produced character sketches of each person.

2) They were told that 5 such descriptions had been randomly selected and that they should rate, from 0-100, the likelihood that each sketch described one of the engineers

3) Ps assess the extent to which the description of Jack is similar to each of the two categories – lawyers and engineers

(To the extent that Jack is more similar to the stereotypical engineer, he is more likely to be judged an engineer)

4) Because this assessment of similarity is independent of the prevalence of lawyers and engineers in the population, the resulting probability judgment is independent of the base rates for these two professions

5) Some participants were told that the population from which the descriptions were drawn consisted of 30 engineers and 70 lawyers. Others were told that the population comprised 70 engineers and 30 lawyers. That is, Kahneman and Tversky manipulated the base rates for the two possible outcomes.

Question 38

Describe the results of Kahneman and Tversky’s (1973) study on base rate neglect

Answer 38

1) 55% of Ps judged the probability that Jack is an engineer when they were told that the population from which the descriptions were drawn consisted of 70 engineers and 30 lawyers

2) 50% of Ps judged the probability that Jack is an engineer when they were told that the population from which the descriptions were drawn consisted of 30 engineers and 70 lawyers

Question 39

Define base rate neglect

Answer 39

People’s tendency to ignore relevant statistical information in favor of case-specific information

Question 40

1) 55% of Ps judged the probability that Jack is an engineer when they were told that the population from which the descriptions were drawn consisted of 70 engineers and 30 lawyers

2) 50% of Ps judged the probability that Jack is an engineer when they were told that the population from which the descriptions were drawn consisted of 30 engineers and 70 lawyers

What do these results suggest?

Answer 40

The personality description might provide some information about Jack’s likely occupation, but this should be combined with information about the number of engineers and lawyers in the population from which his description was randomly drawn.

However, people ignored these base probabilities and simply judged based on the description of Jack only

Question 41

People’s tendency to ignore relevant statistical information in favor of case-specific information

This is known as…?

Answer 41

Base rate neglect

Question 42

Describe Kahneman and Tversky’s (1973) study on base rate neglect part 2

List 4 points

Answer 42

1) Ps were given a list of 9 academic subject areas (e.g., computer science, medicine, law, humanities).

2) The prediction group was told that the sketch of Tom was prepared by a psychologist during
Tom’s final year in high school, and that Tom is now a graduate student. They were asked to rank the 9 academic subjects by the probability that Tom is specialising in that topic, based on his description

Simply = Rank each subject by likelihood Tom is specialising in it

3) The base-rate group was not shown the Tom W. sketch but “consider[ed] all first year graduate students in the US today” and indicated the percentage of students in each of the 9
subject areas – that is, the estimated the base rates for each subject area.

Simply = Estimate what percentage of all students study this topic

4) The representativeness group ranked the 9 subject areas by the degree to which Tom W. “resembles a typical graduate student” in that subject area

Simply = Rank each subject by how representative Tom is of a typical student

Question 43

Describe the results of Kahneman and Tversky’s (1973) study on base rate neglect part 2

List 2 points

Answer 43

1) Across the 9 subjects, probability judgments (mean likelihood rank) were very positively correlated with representativeness judgments or mean similarity rank (r = .97) but negatively correlated with mean estimated base-rate (r= -.65)

2) Predictions were based on how representative people perceive Tom W. to be of the various fields, and ignored the prior probability that a randomly-selected student would belong to those fields (base rate neglect).

Question 44

Judgments based on representativeness will be largely independent of …?

Answer 44

Base rates

Question 45

Judgments based on representativeness will be largely dependent of base rates

True or False?

Answer 45

False

So, judgments based on representativeness will be largely independent of base rates

Question 46

Define the Anchor-and-Adjust heuristic

Answer 46

Judgments are produced by adjusting from a (potentially irrelevant) starting value (anchor), and these adjustments are often insufficient

Question 47

Judgments are produced by adjusting from a (potentially irrelevant) starting value (anchor), and these adjustments are often insufficient

This is known as…?

Answer 47

Anchor-and-Adjust heuristic

Question 48

A pervasive cognitive bias that causes us to rely too heavily on information that we received early in the decision-making process

This is known as…?

Answer 48

Anchoring

Question 49

What is anchoring?

Answer 49

A pervasive cognitive bias that causes us to rely too heavily on information that we received early in the decision-making process

Question 50

Describe Tversky and Kahneman’s (1974) study on anchoring

List 2 points

Answer 50

1) Experimenters span a wheel of fortune that landed on 10 (a low anchor) for one group of participants and on 65 (a high anchor) for another group.

2) Ps were asked whether the proportion of African Countries in the United Nations was more or less than the anchor, and then asked for their best estimate of the true value.

e.g. Is the percentage of African countries in the UN:

a. More or less than 65%? What is your best estimate?
b. More or less than 10%?
What is your best estimate?

Question 51

Describe the results of Tversky and Kahneman’s (1974) study on anchoring

List 2 points

Answer 51

1) The median estimate was 25% in the low anchor condition (more or less than 10%) and 45% in the high anchor condition (more or less than 65%)

2) Ps judgments were pulled towards the anchor values

Simply = Random anchor values can influence your estimates

Question 52

Describe Chapman and Johnson’s (1999) study on anchoring

List 2 points

Answer 52

1) Ps wrote down the last 2 digits of their social
security number and treat it as a probability (e.g., “34%”).

2) Ps were asked whether the probability that a Republican would win the 1996 US Presidential Election was more or less than this probability (e.g. 34%), prior to giving their best estimate of the true probability

Question 53

Describe the results of Chapman and Johnson’s (1999) study on anchoring

Answer 53

The larger the anchor number, the larger the best estimate, with a correlation of r = 0.45.

e.g. 14% vs 54% = Ps with 54% as their anchor made larger estimates

Question 54

What do we use anchoring for?

Answer 54

An initial estimate of the target value and adjust from that starting point in the right direction

Question 55

We use anchoring as an initial estimate of the target value and adjust from that starting point in the right direction

Why?

Answer 55

Because the adjustment is effortful, we often adjust insufficiently and so our judgment is biased towards the anchor value

Question 56

If your anchor value is above the true value, your adjusted estimate value would be…?

Answer 56

Above the true value

Question 57

If your anchor value is below the true value, your adjusted estimate value would be…?

Answer 57

Below the true value

Question 58

What 3 things have little effect on anchoring accuracy?

Answer 58

1) Incentives
2) Warnings
3) Cognitive capacity

Question 59

What are the 3 mechanisms that contribute towards anchoring effects?

Answer 59

1) The idea that consideration of the anchor as a possible value for the estimated quantity activates relevant semantic knowledge

(e.g., when considering 12% as a possible probability for the probability of a Republican win, we call to mind relevant info about the state of the economy, public perceptions of the candidates etc; this activated knowledge then shapes or biases our final estimate)

2) The idea that an anchor value changes our perception of the magnitude of other candidate values (e.g., if we’ve just been thinking about a 12% probability, 50% seems quite large; if we’ve been considering 88%, 50% seems quite small).

3) The idea that externally-presented anchors may be seen as a “hint” or suggestion, even if they are ostensibly uninformative (after all, doesn’t the fact that the experimenter is getting me to consider a number generated by a wheel of fortune suggest that they want me to be influenced by it in some way?)

Question 60

What effect does warning people about anchoring effects and/or giving them an incentive to be accurate have?

Answer 60

It has little effect on the extent to which people anchor on the provided value, which doesn’t fit with the idea that the anchoring effect reflects a “lazy” or “intuitive” judgment system that can be over-ridden by effortful deliberation

Question 61

Some researchers treat bias as error that results from
“____” processing

Answer 61

Lazy

Question 62

What 3 types of heuristics violate rational prescriptions because the human judge has adopted a quick-and-dirty strategy rather than a more effortful consideration of relevant material?

Answer 62

1) Availability
2) Representativeness
3) Anchor and Adjust

Question 63

What are the 2 types of Ecological rationality?

Answer 63

1) Natural Frequencies
2) Misperception of randomness

Question 64

1) Natural Frequencies
2) Misperception of randomness

These are types of…?

a. Heuristics
b. Ecological rationality

Answer 64

b. Ecological rationality

Question 65

What is the natural frequency effect?

Answer 65

When people are better able to solve descriptive Bayesian inference tasks when represented as joint frequencies obtained through natural sampling, known as natural frequencies, than as conditional probabilities

Question 66

When people are better able to solve descriptive Bayesian inference tasks when represented as joint frequencies obtained through natural sampling, known as natural frequencies, than as conditional probabilities

This is known as…?

Answer 66

Natural frequency effect

Question 67

People are more likely to perform well in a task that involves:

a. Probability e.g.70% of people

b. Frequency obtained e.g. 5/10 people

Answer 67

b. Frequency obtained e.g. 5/10 people

Question 68

Some researchers argue that people do much better at probability tasks when the information is
presented in way that matches our supposed “evolved” cognitive capacities for handling this kind of information.

In particular, it has been argued that humans evolved to process frequencies (counts)
obtained by sampling the environment, rather than normalised probabilities

This is known as…?

Answer 68

Natural frequency effect

Question 69

Describe Eddy’s (1982) study on the natural frequency effect

Answer 69

Ps were asked to calculate the probability that a woman has breast cancer, based on the statistics (%) given in the description

e.g. 32% of people

Question 70

Describe the results of Eddy’s (1982) study on the natural frequency effect

List 4 points

Answer 70

1) 95 out of 100 gave estimates between 0.70 and
0.80 when the actual answer was only 0.075. Only 8% gave the correct answer.

2) An estimate of 80% demonstrates the inverse fallacy: it confuses the probability of a positive
test result given the presence of cancer, p(positive|cancer), with the probability of cancer given the positive test result, p(cancer|positive)

3) These probabilities are not the same: the chances of cancer given a positive test depend on the base rate (prior probability) of cancer in the population.

4) A positive test is more likely to indicate cancer when cancer is widespread than when it is very rare.
But the physicians (and most people) tend to ignore this base rate information

Question 71

What did Gigerenzer et al. argue on the natural frequency effect?

List 2 things

Answer 71

1) Probability theory and normalised probabilities are recent

2) We are much better at tracking natural frequencies (because people have not adapted to understanding complex statistics right off the bat)

Question 72

According to Gigerenzer et al., probabilities only make sense when conceived as …?

Answer 72

Longrun frequencies, and that it does not make sense to talk about the probability of a one-off event

(e.g., that a given person has a disease)

Question 73

Gigerenzer argues that humans evolved to keep track of _______, estimated over time by “natural sampling”

(i.e., encountering different types of events and remembering the number of times they occur)

Answer 73

Event frequencies

Question 74

1) Probability theory and normalised probabilities are recent

2) We are much better at tracking natural frequencies (because people have not adapted to understanding complex statistics right off the bat)

What does this relate to?

a. Availability
b. Natural Frequencies
c. Anchor and adjust
d. Misconception of randomness

Answer 74

b. Natural Frequencies

Question 75

Describe Hoffrage & Gigerenzer’s (1998) study on natural frequencies

Answer 75

Ps were asked to calculate the probability that a woman has breast cancer, based on frequencies (counts) given in the description

e.g. 10 out of 1000 people

Question 76

Describe the results of Hoffrage & Gigerenzer’s (1998) study on natural frequencies

Answer 76

46% of physicians answered correctly when the description followed the natural frequency format, compared to only 8% of physicians answered correctly in the original wording of the task

Question 77

46% of physicians answered correctly when the description followed the natural frequency format, compared to only 8% of physicians answered correctly in the original wording of the task

How come calculating probability using frequencies is easier than statistics?

Answer 77

Because it is easier to solve: true positives divided by the total number of positives

There is no need to keep track of the base rate, explaining base-rate neglect when problems are presented in standard probability format

Question 78

46% of physicians answered correctly when the description followed the natural frequency format, compared to only 8% of physicians answered correctly in the original wording of the task

How come calculating probability in the original format is more difficult than statistics?

Answer 78

Because the use of normalised probabilities (which necessitate the explicit incorporation of base rates/priors) deviates from how we “naturally”
evaluate chance

Question 79

What is the alternative explanation for why the natural frequency format makes the task easier?

Answer 79

It simply clarifies the set relations between the various event categories, and that any manipulation which achieves this will have the same beneficial effect

Question 80

What is gambler’s fallacy?

Answer 80

A belief that a random event is less or more likely to happen based on the results from a previous series of events

Question 81

A belief that a random event is less or more likely to happen based on the results from a previous series of events

This is known as…?

Answer 81

Gambler’s fallacy

Question 82

Gambler’s fallacy is part of…?

a. Availability
b. Natural Frequencies
c. Anchor and adjust
d. Misconception of randomness

Answer 82

d. Misconception of randomness

Question 83

Describe Croson and Sundali’s (2005) study on gambler’s fallacy

List 3 points

Answer 83

1) Examined roulette betting patterns from a Nevada casino

2) They focused on “even money” outcomes (where the two outcomes are equally likely, such as “red or black” or “odd or even”; if you bet on the right outcome, you get back twice what you staked)

3) Looked at bets as a function of the number of times that an outcome had occurred in a row (e.g., a streak of two would mean that the last two spins both came up heads or both came up tails)

Question 84

Describe the results of Croson and Sundali’s (2005) study on gambler’s fallacy

List 3 points

Answer 84

1) As the run-length increased, people were increasingly likely to bet that the next outcome would be the opposite of the streak

2) After a run of 6 or more, 85% of bets were that the streak would end, even though this probability remains fixed at .50.

3) 15% of gamblers bet the streak would continue

Question 85

Look at this scenario:

The Number 53 in a lottery in Italy has not come up in 2 years

People bet more than 2.4 billion GBP hoping that number 53 would show up

But actually, nothing can predict that the number could show up

This is an example of…?

Answer 85

Gambler’s fallacy

Question 86

Describe the findings of Tversky and Kahneman’s (1971) study on gambler’s fallacy and representativeness

List 2 points

Answer 86

1) People expect a “local” sequence to be representative of the underlying process

2) i.e. I know that a coin should, in the long run, produce equal numbers of heads and tails, so I expect any sequence of coin tosses to have this property. A run of heads means that a tails outcome will make the local sequence more representative of the data-generating process

Simply = HHHHHT is not as representative as HTHTTH

Question 87

The gambler’s fallacy is often attributed to the _______ heuristic

a. Availability
b. Anchoring
c. Representativeness

Answer 87

c. Representativeness

Question 88

I know that a coin should, in the long run, produce equal numbers of heads and tails, so I expect any sequence of coin tosses to have this property. A run of heads means that a tails outcome will make the local sequence more representative of the data-generating process

Simply = HHHHHT is not as representative as HTHTTH

This is an example of…?

Answer 88

When the gambler’s fallacy is attributed to the representativeness heuristic

Question 89

Describe Ayton and Fischer’s (2004) study on misconception of randomness with past experience

List 2 points

Answer 89

1) Ps watched the TV and ate skittles (took skittles and not put them back in the bowl)

2) Ps had to calculate the probability of picking a specific colour skittle (e.g. Blue) from the bowl without replacement every time they ate a skittle

Question 90

Many physical processes involve sampling with replacement, which results in a consistent probability for a given outcome the more times that it has occurred

True or False?

Answer 90

False

Many physical processes involve sampling without replacement, which results in diminishing probability for a given outcome the more times that it has occurred

Question 91

If you rummage blindly in your cutlery drawer for spoons, removing the spoons as you find them, then the probability that the next item will be a spoon _______ as your hunt progresses.

a. Decreases
b. Stays the same
c. Increases

Answer 91

a. Decreases

Question 92

What did Ayton and Fischer’s (2004) study on misconception of randomness with past experience conclude?

List 2 points

Answer 92

1) Inappropriate generalisation of past experience

2) Random mechanical outcomes = Sampling without replacement

Question 93

How can we induce random mechanical outcomes ?

Answer 93

Sampling without replacement

Question 94

1) With an infinitely long sequence of coin flips, all sequences of a given length occur with _______

e.g., the sequence HHHH will occur with the same frequency as HHHT, so believing that a
run of heads means it’ll be tails next time is indeed a fallacy

Answer 94

Equal probability

Question 95

What are the 3 types of misperception of randomness?

Answer 95

1) Past experience
2) Memory constraints
3) Gambler’s fallacy

Question 96

The sequence HHHH will occur with the same frequency as HHHT, so believing that a
run of heads means it’ll be tails next time is a ______

Answer 96

Fallacy

Question 97

Hahn and Warren (2009) looked at the properties of fair coin under realistic conditions

What were their conclusions?

List 2 points

Answer 97

1) People only ever see finite sequences

2) People can only hold a short subsection of a sequence in memory (e.g., the last 4 outcomes)

Question 98

Hahn and Warren (2009) noted that humans do not experience or remember …?

a. Short sequences
b. Long sequences

Answer 98

b. Long sequences

Question 99

Describe Hahn and Warren’s (2009) study and findings on memory constraints

List 2 points

Answer 99

1) Simulated 10,000 sequences of 10 coin flips

2) The pattern HHHH only appeared in about 25% of the sequences, whereas HHHT occurred in about 35% of the simulated samples.

Simply = If we had 10,000 people each of whom had experienced 10 flips of a fair coin, it would be perfectly reasonable for more of them to expect a sequence HHH to end with a T than with another H.

Question 100

Hahn and Warren (2009) noted that for shorter sequences, the probability of encountering HHHT and HHHH are…?

a. Not equal
b. Equal

Answer 100

a. Not equal

Question 101

The pattern HHHH only appeared in about 25% of the sequences, whereas HHHT occurred in about 35% of the simulated samples, when flipping a coin

What does this suggest?

Answer 101

If we had 10,000 people each of whom had experienced 10 flips of a fair coin, it would be perfectly reasonable for more of them to expect a sequence HHH to end with a T than with another H.

Question 102

True or False?

The brain is lazy

Answer 102

False

The brain is not lazy

The supposed “fallacies” of human judgment and decision-making are often perfectly rational given the finite and imperfect information afforded by the environment and our limited mental capacities

Simply = The brain can think rationally and make careful judgements but it has working memory capacity and can only see finite sequences

Question 103

What are the 2 biases of the availability heuristics?

Answer 103

1) Conjunction Fallacy
2) Under and over estimation

Question 104

1) Conjunction Fallacy
2) Under and over estimation

These are biases of…?

a. Anchoring
b. Availability
c. Representativeness

Answer 104

b. Availability

Question 105

1) Base Rate Neglect
2) Gambler’s Fallacy

These are biases of…?

a. Anchoring
b. Availability
c. Representativeness

Answer 105

c. Representativeness

Question 106

What are the 2 biases of the representativeness heuristics?

Answer 106

1) Base Rate Neglect
2) Gambler’s Fallacy

Question 107

Identify the 2 different theoretical approaches to errors in probability judgment

Answer 107

1) Heuristics & Biases
2) Ecological Rationality

Question 108

Bayes theorem tells us how to update an estimate based on ______ and _______

Answer 108

Existing and new knowledge

Question 109

Bayes theorem tells us how to __________ based on existing and new knowledge

Answer 109

Update an estimate

Question 110

True or False?

Human probability judgments always follow the laws of probability

Answer 110

False

Human probability judgments do not always follow the laws of probability, and these deviations illuminate the judgment process

Question 111

One broad framework posits the use of simplifying strategies that reduce effort at the expense of sometimes introducing bias

This is known as…?

Answer 111

Heuristics

Question 112

People sometimes simplify judgments by substituting an easier-to-evaluate entity for the target dimension

Give 2 examples of this

Answer 112

1) Availability Heuristics
2) Representativeness Heuristics

Question 113

Judgments often assimilate towards ______ values

Answer 113

Anchor

Question 114

We can also consider probability judgments in their ecological context

How?

Answer 114

One idea is that humans evolved to process frequencies, not normalising probabilities, although this interpretation of frequency-format effects is debatable

Question 115

The gambler’s fallacy reflects ecological experience with …?

Answer 115

Different types of generating processes

Question 116

The gambler’s fallacy reflects _______ experience with different generating processes.

Answer 116

Ecological