2.1 Problem 7
Part A
Judgement- deciding on the likelihood of various events using incomplete information
Important aspect= accuracy
Forms important initial part of decision making
Decision making- selecting one option from several possibilities
Factors involved in decision-making depend on important of decision
Problem-solving differs in individuals must generate own solution, rather than
choosing presented options
Typically assess decision quality in terms of consequences
o Good if given info available at time, even if consequences are poor
Judgement Research
Subjective assessment of probability of something, often changed by new info
New info increases or decreases strength of our beliefs
Bayes (Bayesian inference)
- Situations where 2 possible subjective beliefs of hypotheses
- Showed how new data or info changes subjective probabilities of each
hypothesis being correct
Bayes theorem: need to evaluate beliefs concerning relative probabilities of 2
hypotheses before data are obtained
Need to calculate relative probabilities of obtaining the observed data under each
hypothesis (likelihood ratio)
Kahneman & Tversky- Bayes theory
Method: Cab involved in accident one night
85% belonged to Green company, 15% to Blue company
Results: Eyewitness identified cab as Blue cab
Ability to identify cabs under similar visibility conditions test, she
was wrong 20% of the time
Probability for blue cab is .15, for green cab is .85: probability of
eyewitness identifying cab as blue when it was Blue= .80
Probability for Blue cab when it was Green= .20
Ignored base-rate info about number of cabs as hard for
participants to see causal structure
Individuals making judgements should take account of base-rate information-
relative frequency of event within a given probability
o Usually ignore this info or de-emphasise it
Recency and familiarity produce a distortion in frequency estimation, increasing
or decreasing availability
o Eg. estimations of populations vary dependent on the media cover about
them
Heuristics
Tversky and Kahneman
Most people given judgement tasks us heuristics (-strategies that ignore part of
info with goal of making decisions more quickly, frugally, and or accurately than
more complex methods
o Greatly reduce effort associated with cognitive tasks
Can lead us to ignore base-rate info
o Use representativeness heuristics- deciding an object or person
belongs to a given category because it appears typically or representative
of that category
Conjunction fallacy- mistaken belief that the conjunction or combination of two
events is more likely than one event on its own
o still occurs even when everything is done to ensure people interpret
problem correctly
, o Explanation of C.F assume occurs due to high perceived probability of
additional info given the description
Availability Heuristic
Availability heuristic- frequencies of events can be estimated by how easy or hard it is
subjectively to retrieve them from long term memory
Liechtenstein Et Al.
Method: Judge likelihood of different causes of death
Results: attracting much publicity, judged more likely that those that do not, even
when opposite is true
Pachur et Al.- can explain people’s judged frequencies of various causes of death in three
ways
1. Use availability heuristic based on own direct experience
Best predictor of judged frequencies of different causes
2. Use availability heuristic based on media coverage of causes of death + own
experience
Least successful predictor
3. Use affect heuristic- influences many judgements
Predicted by judged risks
Oppenheimer:
Method: pairs of names, one famous, one non-famous
Asked to indicate which was more common
Results: Selected non-famous ones
if using availability heuristic, would select famous ones
participants used deliberate thought to override availability heuristic
Significance: availability heuristic can sometimes be overridden
Individuals often rely on available info even when have knowledge indicating they
shouldn’t
Observed in everyday situation
Study: married partners individually state which of them performed more
of household chores
Results: each stated he or she mero around 4 fifths of the chores
Significance: may engage in using availability heuristic when it confirms
their beliefs about themselves
Anchoring-and-Adjustment Heuristic
Anchoring-and-Adjustment Heuristic- use an initial estimate (anchor) then adjust it
to produce final estimate: adjustment typically insufficient
Effects occur in many settings eg. art auction, anchor price towards price
achieved in previous auctions
Operates even when anchor is arbitrary or impossibly extreme
Both novices and experts
Likely anchor restricts search for relevant info in memory
o Concentrate search on info close to anchor, even if this isn’t realistic
Use when estimating confidence intervals: supply range that is too narrow
can overcome these by thinking about initial estimate, ask whether paying
enough attention to feature of this specific situ
Recognition heuristics
Occurs during comparison of relative frequency of 2 categorises: recognise one
category but not the other, conclude that recognised category has highly
frequency
Framing
Framing effects- the way that options are presented influences the selection of an
option
Tend to choose options offering a small but certain gain, rather than larger but
uncertain gain
o Unless uncertain gain is either tremendously greater, or modestly less than
certain
Part A
Judgement- deciding on the likelihood of various events using incomplete information
Important aspect= accuracy
Forms important initial part of decision making
Decision making- selecting one option from several possibilities
Factors involved in decision-making depend on important of decision
Problem-solving differs in individuals must generate own solution, rather than
choosing presented options
Typically assess decision quality in terms of consequences
o Good if given info available at time, even if consequences are poor
Judgement Research
Subjective assessment of probability of something, often changed by new info
New info increases or decreases strength of our beliefs
Bayes (Bayesian inference)
- Situations where 2 possible subjective beliefs of hypotheses
- Showed how new data or info changes subjective probabilities of each
hypothesis being correct
Bayes theorem: need to evaluate beliefs concerning relative probabilities of 2
hypotheses before data are obtained
Need to calculate relative probabilities of obtaining the observed data under each
hypothesis (likelihood ratio)
Kahneman & Tversky- Bayes theory
Method: Cab involved in accident one night
85% belonged to Green company, 15% to Blue company
Results: Eyewitness identified cab as Blue cab
Ability to identify cabs under similar visibility conditions test, she
was wrong 20% of the time
Probability for blue cab is .15, for green cab is .85: probability of
eyewitness identifying cab as blue when it was Blue= .80
Probability for Blue cab when it was Green= .20
Ignored base-rate info about number of cabs as hard for
participants to see causal structure
Individuals making judgements should take account of base-rate information-
relative frequency of event within a given probability
o Usually ignore this info or de-emphasise it
Recency and familiarity produce a distortion in frequency estimation, increasing
or decreasing availability
o Eg. estimations of populations vary dependent on the media cover about
them
Heuristics
Tversky and Kahneman
Most people given judgement tasks us heuristics (-strategies that ignore part of
info with goal of making decisions more quickly, frugally, and or accurately than
more complex methods
o Greatly reduce effort associated with cognitive tasks
Can lead us to ignore base-rate info
o Use representativeness heuristics- deciding an object or person
belongs to a given category because it appears typically or representative
of that category
Conjunction fallacy- mistaken belief that the conjunction or combination of two
events is more likely than one event on its own
o still occurs even when everything is done to ensure people interpret
problem correctly
, o Explanation of C.F assume occurs due to high perceived probability of
additional info given the description
Availability Heuristic
Availability heuristic- frequencies of events can be estimated by how easy or hard it is
subjectively to retrieve them from long term memory
Liechtenstein Et Al.
Method: Judge likelihood of different causes of death
Results: attracting much publicity, judged more likely that those that do not, even
when opposite is true
Pachur et Al.- can explain people’s judged frequencies of various causes of death in three
ways
1. Use availability heuristic based on own direct experience
Best predictor of judged frequencies of different causes
2. Use availability heuristic based on media coverage of causes of death + own
experience
Least successful predictor
3. Use affect heuristic- influences many judgements
Predicted by judged risks
Oppenheimer:
Method: pairs of names, one famous, one non-famous
Asked to indicate which was more common
Results: Selected non-famous ones
if using availability heuristic, would select famous ones
participants used deliberate thought to override availability heuristic
Significance: availability heuristic can sometimes be overridden
Individuals often rely on available info even when have knowledge indicating they
shouldn’t
Observed in everyday situation
Study: married partners individually state which of them performed more
of household chores
Results: each stated he or she mero around 4 fifths of the chores
Significance: may engage in using availability heuristic when it confirms
their beliefs about themselves
Anchoring-and-Adjustment Heuristic
Anchoring-and-Adjustment Heuristic- use an initial estimate (anchor) then adjust it
to produce final estimate: adjustment typically insufficient
Effects occur in many settings eg. art auction, anchor price towards price
achieved in previous auctions
Operates even when anchor is arbitrary or impossibly extreme
Both novices and experts
Likely anchor restricts search for relevant info in memory
o Concentrate search on info close to anchor, even if this isn’t realistic
Use when estimating confidence intervals: supply range that is too narrow
can overcome these by thinking about initial estimate, ask whether paying
enough attention to feature of this specific situ
Recognition heuristics
Occurs during comparison of relative frequency of 2 categorises: recognise one
category but not the other, conclude that recognised category has highly
frequency
Framing
Framing effects- the way that options are presented influences the selection of an
option
Tend to choose options offering a small but certain gain, rather than larger but
uncertain gain
o Unless uncertain gain is either tremendously greater, or modestly less than
certain
