Lecture 3

Question 1

Tunnel vision

Answer 1

You’re looking for information that is in line with your own theory

Question 2

Bias in sample

Answer 2

Too small size, selective sample

Question 3

Bias in base rates

Answer 3

The base rate fallacy, also called base rate neglect or base rate bias, is a type of fallacy in which people tend to ignore the base rate (i.e., general prevalence) in favor of the individuating information (i.e., information pertaining only to a specific case).

Example: What is an example of base rate neglect bias?
When asked what the probability is that the cab involved in the hit and run was green, people tend to answer that it is 80%. However, this ignores the base rate information that only 15% of the cabs in the city are green.

Or for joris who is boring and likes to read, you would say he is a librerian, but if you think about how many construction workers we have in the netherlands, he is probably a construction worker.

Question 4

Law of large numbers

Answer 4

Outcomes become closer to the
expected value with more trials

Question 5

Gambler’s fallacy

Answer 5

if a particular event, occurs more frequently than normal during the past, it is less likely to happen in the future, even when the events are statistically independent

Question 6

Regression Effect

Answer 6

Extreme effects will, on average, be less extreme at another point in time.

Effect applies to stable contrext. When there is an unstable context, extreme observation van be indicative of change –? new change or less sick!

Question 7

Anchoring and adjustment

Answer 7

people give too much weight to the first bit of data for their quantitative estimates.

Question 8

Anchroing condition 1:
→ Question 1
→ Is the average price of a German car higher or lower
than 20,000 Euros?
□ lower than 20,000 Euros
□ higher than 20,000 Euros
→ Question 2
→ What is the average price of a German car?
Participants estimated 32,000 Euros

condition 2:
→ Question 1
→ Is the average price of a German car higher or lower
than 40,000 Euros?
□ lower than 40,000 Euros
□ higher than 40,000 Euros
→ Question 2
→ What is the average price of a German car?
Participants estimated 37,000 Euros (5,000 Euro more)

Answer 8

conclusion: anchoring helps haha

Question 9

why does anchoring occur?

Answer 9

• assimilation of quantitative estimates to an available comparison figure (also with numbers that are irrelevant to the decision). In the book there was this wheel of fortune, and participant would answer a higher numbe rif they actuallyhad invested more money in this wheel of fortune.

Question 10

Explanations of anchoring:

Answer 10

• initial hypothesis = anchoring balue, then people adjust too little
• anchors make different types of information accessible, that are then used in the judgement

Question 11

Anchoring: accessibility explanation. How can you explain this with the two conditions about the german cars?

Answer 11

→ Condition 1: Is the average price of a German car higher or lower than 20,000 Euros? –> people will start to think more about a volkswagen gold
→ Condition 2: Is the average price of a German car higher or lower than 40,000 Euros? –> people will start to think more about a mercedes for example.

Question 12

Lexical decision task. conclusions?

Answer 12

• task measure cognitive accessibility
• existing word –> “yes” button (as fast as possible)
• non-existing word –> no button as fast as possible

→ More accessible words are recognised more quickly as being existing words
→ In the 20,000 Euros condition participants recognised cheaper car brands (Opel, Golf) faster
→ Greater chance that this information is retrieved from memory and used to
make an estimate
→ This is why the estimate was lower
→ In the 40,000 Euros condition participants recognised expensive car brands (BMW, Mercedes) faster
→ etc.

Question 13

What helps with anchoring?

Answer 13

• shaking your head helps a bit
• just leave the negotiation
• experts are still influenced by anchoring

Question 14

availability heuristic

Answer 14

For example with jaws: People who watched the film Jaws were more likely to overestimate the number
of shark deaths per year than people who had watched another film

• easier to come up with examples of event –> event is estimated to be more probable

→ Subjective ease counts, not number of retrieved examples
→ Examples of assertiveness 12 vs. 6

→ Often leads to good estimates but familiarity and vividness of
information can bias estimates
→ number of people who are members of a student club in Leiden is
overestimated. Shark attacks or lightning deaths are
overestimated.

Question 15

Risk perception

Answer 15

people will think things like plane crashes and terror attacks are more risky, ust because of the vividly gore. for example.

Question 16

Simulation Heuristic

Answer 16

→ The generation (mental simulation) of events
→ Guides expectations, motivation, behaviour
→ Particularly with missed opportunities
→ Counterfactual thinking
→ Simulation of alternative results (“if only I had…”)
→ The easier it is –> the greater the dissapointment

Question 17

Medvec, Madey, & Gilovic (1995), about study with medal winners

Answer 17

→ Participants rated emotions of medal winners during prize ceremonies
→ Bronze winners look happier than silver winners (i.e., “gold losers”)

Question 18

Representativeness Heuristic

Answer 18

The more characteristics @ shares with B (behaviour) the more likely people think that A and B are associated

• b can be the consequences of A, (because Joris is a liberian and he likes to read)
• B can be an exemplar of category A: boring, tidy and enjoying reading has a lot in common with a librarian. Observed probability is greater that Joris works in a library than in constrction

Question 19

Representativeness heuristic also for eents, for example roulette. why?

Answer 19

brbrbrbrb, bbbbrrrr and bbbbbb

Each option is equally likely, but option A is more representative: it looks like the most random option

Question 20

Conjunction Fallacy

Answer 20

The conjunction fallacy (also known as the Linda problem) is an inference from an array of particulars, in violation of the laws of probability, that a conjoint set of two or more conclusions is likelier than any single member of that same set. It is a type of formal fallacy.

The most often-cited example of this fallacy originated with Amos Tversky and Daniel Kahneman.[2][3][4]

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.

Which is more probable?

Linda is a bank teller.
Linda is a bank teller and is active in the feminist movement.
The majority of those asked chose option 2. However, the probability of two events occurring together (that is, in conjunction) is always less than or equal to the probability of either one occurring alone

Question 21

study less is more, when persons read positive features, negative features and information gets added. what happens?

Answer 21

Everytime when information got added:

positive features: people would rate a less positive impression of a person when there were moderatly positive features got added.

With negative features, people got rated more positively if information got added (like moderately negative features)

So basically: the effect gets evened out.

Question 22

Dilution effect:
→ Information
→ 35 years old
→ Man
→ Unmarried
→ Unemployed
→ Drinks alone
→ Gets drunk at parties
→ He’s an alcoholic (quite sure!)

let’s add more info:
→ Information
→ 35 years old
→ Lawyer
→ Unmarried
→ Listens to classical music
→ Unemployed
→ Drives a red Toyota
→ Drinks alone
→ Reads “the economist”
→ Gets drunk at parties
→ Perhaps an alcoholic? (not so sure…)

what can we conclude?

Answer 22

→ Diagnostic information diluted (‘verdund’) with non-diagnostic information
→ Judgement becomes more moderate and less certain
→ Conjunction is often ‘more diagnostic’
→ Especially in observers who are motivated to form an accurate impression!

Question 23

Decoy effect (A 4.00, B 6.50 and C 7,00)

Answer 23

• Consumers change preference due to a dominated alternative
• A dominates b in terms of price, but not in volume
• C dominates B in volume, and relative price

Question 24

Dijksterhuis (2004) about rating the 4 student apartments: → 12 pieces of info (positive/negative) for each apartment (e.g. “attractive
neighbourhood” or “unfriendly landlord”)
→ One apartment is best (8 pos., 4 neg.)
→ One apartment is worst (4 pos., 8 neg.)
→ Two apartments are in between (6 pos., 6 neg.)
→ Three conditions
1. Rate immediately (
2. Think about it for three minutes, then rate (conscious thoughts)
3. Filler task to prevent conscious thoughts, then rate (unconscious thoughts)

Conclusion?

Answer 24

With the filler task, conscious thinking gets filtered out.

with complex decisions (too difficult to think about consciously). Ikea is too xomplex indeed, and people were more msatisfied with their purchase than when they bought something at Bijenkorf.

Sometimes we need our unconcious mind to do the work.
Satisficing is about choosing the first option that satisfy you, which can help!