Reasoning and decision making
Reasoning
Conclusions beyond info provided
Deductive reasoning
Inductive reasoning
Decision making
Make choices
Psychology research question?
Do people think logically?
How well can people evaluate problems?
How do we represent information?
What are the biases in reasoning?
Decision making
Utility approach
If have all information, will choose
most desirable outcome
Complicated what is valuable:
Not all pieces can be calculated
Potential for inaccurate mental
simulations
Poor at predicting emotional reactions
Reasoning and decision making
Heuristics
Bias
Representativeness heuristic
Availability heuristic
Anchoring and adjustment
Framing effect
Confirmation bias
Reasoning problem
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A nearby town is served by 2 hospitals. About 45
babies are born each day in the larger hospital.
About 15 babies are born each day in the smaller
hospital. Approximately 50% of all babies are boys.
However, the exact percentage of babies who are
boys will vary from day to day. Some days it may be
higher than 50%, some days lower. For a period of 1
year, both the larger and smaller hospital recorded
the number of days on which more than 60% of
babies born were boys. Which hospital do you think
recorded more such days?
Larger hospital
Smaller hospital
About the same (within 5% of each other)
Representativeness heuristic
Which outcome is more likely?
THHTHT or HHHTTT
THHTHT judged as representative of “random”
Judgment of similarity to general category
Small-sample fallacy
Hospital problem: 56% say same
Ignore law of large numbers
Descriptions change reasoning
Base-rate fallacy
Ignore statistics, decision based on descriptive
information
Linda…
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 she also participated in anti-nuclear
demonstrations.
Rank the following options in terms of the probability of
their describing Linda. Give a rank of 1 to the most likely
option and 8 to the least likely.
Linda is a teacher at an elementary school.
Linda works in a bookstore and takes yoga.
Linda is active in the feminist movement.
Linda is a psychiatric social worker.
Linda is a member of the league of women voters.
Linda is a bank teller.
Linda is an insurance salesperson.
Linda is a bank teller and active in the feminist
movement.
Conjunction fallacy
Tversky & Kahneman (1983)
Most thought teller and feminist more likely
Mathematically less likely – conjunction
Seems more appealing even though
statistically less likely
5
4
3
2
1
0
Bank teller
Bank teller and
feminist
Naïve
Intermed
Sophisticated
Availability heuristic
Are there more words that have K in
the 1st position or 3rd?
“What is more likely…” (e.g. diseases)
Availability heuristic
How easily examples come to mind
Generally correct, but can lead to errors
Factors that influence:
Recency, Familiarity, Knowledge
McKelvie (1997): list of m/f names
12 famous m v. 14 f: 77% report more
males in list
Decision making
Imagine that the US is preparing for the
outbreak of an unusual Asian disease, which
is expected to kill 600 people. Two
programs have been proposed.
A: 200 people will be saved
B: 1/3 probability that 600 will be saved,
but 2/3 probability that no one will be saved
Which program do you favor?
Decision making
Imagine that the US is preparing for the
outbreak of an unusual Asian disease, which
is expected to kill 600 people.
What if 2 different programs are proposed
Opt. C: 400 people will die
Opt D: 1/3 probability that nobody will die
and 2/3 probability that 600 will die
Which program do you favor?
Framing effect
Subtle changes in wording can change
interpretation/decision
Tversky & Kahneman (1981)
A vs. B: focus on lives “saved”
72% chose A: “risk averse”
But, if asked choose between
C: 400 people will die
D: 1/3 probability that nobody will die and 2/3
probability that 600 will die
22% chose C: “risk taking”
Identical deep structures (A/B vs. C/D)
Depends on how question is “framed”
CogLab: Decision making
F’10 data: Problem 1
Imagine the country is preparing for the outbreak of an
unusual disease, which is expected to kill 600 people.
Two alternative programs to combat the disease have
been proposed.
Set 1:
Choice A: If program A is adopted, 200 people will be
saved.
Choice B: If program B is adopted, there is 1/3 probability
that 600 people will be saved and 2/3 probability that no
one will be saved.
83% choice A; 17% choice B
Set 2:
If program A is adopted, 400 people will die.
If program B is adopted, there is 1/3 probability that
nobody will die, and a 2/3 probability that 600 people will
die.
33% choice A; 66% choice B
CogLab: Decision making
F’10 data: Problem 2
Set 1:
Consider the following 2-stage game. In the 1st
stage there is a 75% chance to end the game
without winning anything and a 25% chance to
move into the 2nd stage. If you reach the 2nd stage
you have a choice between the following options.
Your choice must be made before the game begins.
Choice A: A sure win of $30
Choice B: An 80% chance to win $45
83% Choice A; 17% Choice B
Set 2:
Which of the following do you prefer?
Choice A: A 25% chance to win $30
Choice B: A 20% chance to win $45
66% Choice A; 33% Choice B
CogLab: Decision making
F’10 data: Problem 3
Set 1:
Imagine that you are about to purchase a jacket for
$250 and a calculator for $30. The calculator
salesman informs you that the calculator you wish
to buy is on sale for $20 at the other branch of the
store, located 20min away. Would you make the
trip?
Choice A: Yes; Choice B: No
17% Choice A; 83% Choice B
Set 2:
Imagine that you are about to purchase a jacket for
$30 and a calculator for $250. The calculator you
wish to buy is on sale for $240 at the other branch
of the store, located 20min away. Would you make
the trip?
Choice A: Yes; Choice B: No
33% Choice A; 66% Choice B
CogLab: Decision making
F’10 data: Problem 4
Imagine that you have decided to see a play
and paid admission price of the $20 ticket.
As you enter the theater,
Set 1:
you discover that you have lost it. Would you pay
$20 for another ticket?
Choice A: Yes; Choice B: No
33% Choice A; 66% Choice B
Set 2:
you discover that you have lost a $20 bill. Would
you still pay $20 for a ticket to the play?
Choice A: Yes; Choice B: No
100% Choice A; 0% Choice B
CogLab: Decision making
F’10 data: Problem 5
Set 1:
Would you accept a gamble that offers a 10% chance
to win $95 and a 90% chance to lose $5?
Choice A: Yes; Choice B: No
50% Choice A; 50% Choice B
Set 2:
Would you pay $5 to participate in a lottery that offers
a 10% chance to win $100 and a 90% chance to win
nothing?
Choice A: Yes; Choice B: No
33% Choice A; 67% Choice B
Kahneman & Tversky (1984)
Would you accept a gamble that offers a
10% chance to win $95 and a 90% chance
to lose $5?
Would you pay $5 to participate in a lottery
that offers a 10% chance to win $100 and a
90% chance to win nothing?
41% gave different preferences
Even though $5 is loss of gamble vs cost to play
32% said ‘no’ to 1st offer, but ‘yes’ to 2nd
Kahneman & Tversky (1984)
Choose between
A sure gain of $240
25% chance to gain $1000 and
75% chance to gain nothing
Choose between
A sure loss of $750
75% chance to loose $1000 and
25% chance to lose nothing
Kahneman & Tversky (1984)
Choose between
A sure gain of $240
25% chance to gain
$1000 and 75%
chance to gain
nothing
Choose between
A sure loss of $750
75% chance to loose
$1000 and 25%
chance to lose nothing
84% (risk-averse)
16%
13%
87% (risk-seeking)
Framing: medical decisions
McNeil et al (1982)
Hospital physicians asked which form of
treatment for patient with lung cancer (surgical or
6wk radiation)
IV: prior information (framing)
“Of 100 people having surgery, 10 will die during
treatment, 32 will have died by 1yr, and 66 will have
died by 5yrs. Of 100 people having radiation therapy,
none will die during treatment, 23 will have died by
1yr, and 78 will have died by 5yrs.”
“Of 100 people having surgery, 90 will be alive
immediately after treatment, 68 will be alive after 1yr,
and 34 will be alive after 5yrs. Of 100 people having
radiation therapy, all will be alive after treatment, 77
will be alive after 1yr, and 22 will be alive after 5yrs.
Results:
Framed in terms of dying: 44% choose radiation
Framed in terms of living: 18% choose radiation
CogLab: Risky decisions
Sp ‘12
Problems
Get some additional money or lose money
Choices
Risky (probability) vs riskless choice
Hyp
When choices are gains: risk-avoiding
When choices are losses: risk seeking
Expected: % smaller for gain vs loss problems
Results: % risky choice selected
Gain: 48.5% (46% global)
Loss: 12.1% (41% global)
Tversky & Shafir (1992)
Imagine you have just taken a tough exam. It is
the end of the semester, you feel tired and you
find out that you
Passed the exam
Failed the exam and you will have to take it again in a
couple of months
Won’t know the outcome of the exam for 2 more days
You now have the opportunity to buy a 5-day
vacation to Hawaii at a very low price. It expires
tomorrow.
Would you:
Buy the vacation package?
Not buy the vacation package?
Pay a $5 nonrefundable fee in order to retain the right
to buy the vacation at the same price the day after
tomorrow?
Tversky & Shafir (1992)
Pass/fail doesn’t change % of decisions
Each individual needs to have reason for decision!
Justification process
Anchoring and adjustment
Anchor: begin with first approximation
Adjustment: changes based on added info
Multiplication problem: 5s respond
A: 8x7x6x5x4x3x2x1
B: 1x2x3x4x5x6x7x8
A grp median: 2,250
B grp median: 512
Correct answer: 40,320
Real world application
First impressions
Others?
Confirmation bias
Tendency to only gather support; ignore
disconfirming evidence
Wason (1960) card task
You will be given 3 #s which conform to a simple rule.
Your aim is to discover this rule. Write down #s and
reasons and I’ll tell you if they conform to the rule or
not.
Results: Few participants who after they were correct
tried to disconfirm their hypothesis.
Lord et al. (1979)
How convincing an article is depends on prior attitude
Kuhn’s “Structure of a Scientific Revolution”
Reasoning: Bias
Framing
Way alternatives are structured
Consequences are the same
Affects representation
Representativeness heuristic
Decision based on comparison to ideal
Don’t consider statistics
Availability heuristic
Tendency to use answer that easily comes to mind
Anchoring and adjustment
Influenced by starting point of problem
Confirmation bias
Tendency to seek/use info that supports belief
Belief persistence
Neuroeconomics
Economic decision making problems
Examine influence of emotion (and mood) on decisions
Expected emotions (predicted)
Immediate emotions: integral vs incidental
Emotion determines risk aversion (impact of loss greater
than gain)
Sanfey et al (2003)
Ultimatum game (how to split $)
IV: human vs computer partner
Result: humans reject low offers b/c “unfair”
Brain activity: Anterior insula activation when rejected
offer
Lerner et al (2004)
View film (sad, disgust, neutral)
Decision conditions:
Sell: Set price to sell product
Choice: price willing to choose product instead of accepting $
Result: sad/disgust grps set price lower
Neuroscience of thinking
Major area involved: prefrontal
cortex (PFC)
Damage to PFC has effect on:
Planning and perseveration
Problem solving
Understanding stories
Reasoning
Application: teenagers
Why are we imperfect?
Why use heuristics?
Less effort, less to remember
Economical
Faster to answer
Usually correct
Effective
Reduce errors
Approximation
Examples/Problems purposefully created
to create “errors”
Help us understand cognitive process