cog wk 7

Question 1

Availability Heuristic

Answer 1

if something is easy to come to mind, it is perceived to be more frequent

people overestimate rare events, underestimate common events. Rare events we hear in the news more and come to mind more often.

Question 2

Research for Availability Heuristic

Answer 2

p.p either shown 19 famous men or 20 non famous women vice versa people remembered famous names more than non.

81% judged that gender with more famous people were more common (when they were not).

Question 3

Representativeness Heuristic
(base rate neglect)

Answer 3

ignore statistical context.
Instead place into categories and assume characteristics.
e.g. when described a meek man, will assume he is a librarian over a construction worker when construction workers are much more common.

Question 4

Anchoring heuristic

can give example

Answer 4

given an obvious random number. then asked is the likelihood of X more or less than this number. People’s judgement will then be anchored closer to this number.

e.g. they first judge if it is bigger or smaller than the number. then move away. the process of moving away is tiring and so stop too close to anchor.

Incentives, warnings etc have little effect.

Question 5

Ecological Rationality

2 examples

Answer 5

• natural frequencies
• misperception of randomness

explains errors in thinking by looking at informational environments (info being exposed to) rather than judging the brain as “lazy” (as heuristics do)

Question 6

natural frequencies

Answer 6

• instead of 28.5%, say 2 in 7 deer caught.
• this representation is more intuitive to humans
• this representation suggests hunting deer would happen over time across events whereas 28% suggests that you catch 28% or nothing on each day

Question 7

natural frequencies

Gigerenzer argued

Answer 7

we are not adapted to these modern probability theories.
WE are much better at tracking natural frequencies.

Question 8

misperception of randomness

gamblers fallacy

Answer 8

given independent 50/50 probabilities, gamblers will predict that a high streak will end compared to a low streak.

e.g. 5 heads in a row, will predict tails.

even tho the streak of heads has no impact on probability of tails

Question 9

Representaiveness

explanation

Answer 9

people expect local sequence (small) as having properties of a generative frequence (long) so HTTHHT is not as representative of HHHHHT
Tversky & Kahneman (1971)

Question 10

Misperception of randomness
Past Experience

Answer 10

Inappropriate generalization of past experience

Random mechanical outcomes = Sampling without replacement

e.g. eating 4 red sweets from a bag not replacing

Question 11

2 Misperception of randomness
Memory constraints

Answer 11

• humans can only see a finite sequence
• can only hold a short subsection of a sequence in memory (e.g. last 4 outcomes)

Question 12

what biases does the availability heuristic lead to

Answer 12

• Conjunction fallacy
• Under and Over estimation

Question 13

What biases does Representativeness lead to

Answer 13

• Base rate neglect
• Gambler’s fallacy

Question 14

what is bayes theorum

Answer 14

Bayes theorem tells us how to update an estimate based on existing and new knowledge

e.g. A given B = P(A) / …..
from A level stats