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8/12/2019 Decision Making & Reasoning
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Reasoning and DecisionMaking
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Thinking
Ways of thinking
Analysis breaking down a large complex problem intosmaller simpler problems
Synthesis combining two or more concepts into acomplex form
Divergent thinking generating many ideas or possiblesolutions to a problem
Convergent thinking choosing the best solution or ideaof a possible many
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Categories of thinking processes
Problem solving developing a solution to aproblem situation
Judgments and decision making involves
making choices
Reasoning drawing conclusions given specificinformation
Creativity production of original thoughts andideas
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Reasoning
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Two basic processes in reasoning
1. A process that uses existing knowledge toreason or make decisions about new situationsand information acquired during newexperiences.
Top-down process
Errors can lead to top-down errors
2. A process that determines what new
information is relevant to reasoning and decisionmaking
Confirmation bias
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Reasoning and Logic
Two forms to be covered:
Syllogisms a 3-statement logical form, the
1sttwo parts state premises or statementsassumed to be true, and the 3rdpart is aconclusion based on those premises
Conditional reasoning a logical determinationof whether evidence supports, refutes, or isirrelevant to the stated if-then relationship
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Syllogisms
Abstract: All members of category A are members of category B. All members of category B are members of category C Therefore, all members of category A are members of
category C
More concrete example: All psychology students are intelligent All intelligent people are rich Therefore all psychology students are rich
Use of a Venn diagram to determine accuracy ofconclusion
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Conditional Reasoning
An if then statement where the if part isthe antecedent and the then statement isthe consequence If the antecedent is true, the consequence is
true, or
If the antecedent exists, the consequenceexists
Two types of valid inferences Modus ponens
Modus tollens
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Modus Ponens
Affirming the antecedent to be true
Valid inference:
If a person is intelligent, then they are rich.
Mary is intelligent, she is rich
Invalid inference: negating the antecedent
Mary is notintelligent, she is not rich. Wrong
An easier example:
If one kills a lawyer, then she is dead.
Valid: John killed a lawyer, she is dead
Invalid: John did not kill a lawyer, she is not dead
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Modus Tollens
Concerned with the consequence worksopposite to modus ponens
If you kill a lawyer, then she will be dead Invalid inference confirming the consequence
The lawyer is dead, therefore you killed her
Valid inference negating the consequence
The lawyer is not dead, therefore you didnt kill her
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Other examples
If one is intelligent, then one is rich
1. John is rich, therefore he is intelligent
Invalid not all rich people are intelligent
2. John is not rich, therefore he is not intelligent Valid
3. John is intelligent; he is rich
Valid
4. John is not intelligent; he is not rich
Invalid- you do not have to be intelligent to berich
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Problem with the confirmation bias
Problem is we tend to want to affirm ordeny the antecedent and ignore theconsequence
Example: Wasson card problem
Test rule :If a card has a vowel on one side,then it has to have an even number on the
other side.
2ndrule: If a letter is sealed, then it has tohave a 50cent stamp
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Problem with the confirmation bias
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Decisions and Judgments
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Decisions under situations of certainty
You have all the necessary information to make acorrect decision
Frequently studied decisions about physicaldifferences
Our decisions about which stimulus is the brightest ,smallest, heaviest, etc. depends upon factors other thanthe physical difference between them
Example: The determination of which of 2 lights isbrightest depends upon the physical difference, but alsothe absolute brightness of the light, the brightness ofthe background, and how long the lights were visible
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Distance or discrimination effect
The greater the distance or differencebetween two stimuli being compared, thefaster the decision about their differences
Symbolic distance effect comparisonsbetween two symbols that represent twostimuli like drawings Differs from distance effects in that it requires
semantic and other memory processes
Semantic contiguity effect
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Examples
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Judgment and decision making in
situations of uncertainty
The individual is not given all theinformation necessary to be certain of theanswer and has to use previously acquired
knowledge
Primary problem: lack of knowledge andmisinterpretation
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Utility Maximization Theory
Humans attempt to make decisions thatprovide us with the maximum gain
Subjective utility theory modificationthat takes into consideration that humansare not always objective, but takeconsider subjective factors
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Examples of Subjective factors
Satisficing we do not always pursue theoptimal decision, but accept one that isadequate
Immediate benefit versus delayed rewarddiscounting delayed rewards
The way the problem is framed(presented) is important
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Example 1 of framing
You go to New York and decide to go to aBroadway play. You buy a ticket for $100 in themorning, but when you go to the theater thatevening, you discover you have lost the ticket.
You have plenty of money to buy another one:do you?
You go to New York and decide to go to aBroadway play and tickets cost $100. You go to
the theater that evening and when you start topay for your ticket, you discover you have lost$100. You have plenty of money to buy a ticket:do you?
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Example 2 of framing
Subjects has to make 2 decisions:
Decision 1:
A. A sure gain of $240 or B 25% chance of winning $1000 and a 75%
chance of winning nothing
Decision 2:
C. A sure loss of $750 or D. 75% chance of losing$1000 and 25%
chance of losing nothing
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Possible outcomes
A and C:
A sure loss of $510
B and D:
75% chance of losing $1000 and only a 25% chance of
winning not good odds
A and D:
$240 - $1000 = -$760
$240 - $0 = +$240
B and C: $1000 - $750 = +$250
$0 - $750 = -$750
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Use of algorithms
A specific solution procedure that if used correctlyguarantees a correct solution
Identify all possible solutions and try each oneuntil you find the one that works
The use of Algorithms is nottrial and error
Addressed in more detail in problem solving
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Heuristics
A rule of thumb strategy usually a shortcut that generally works in mostsituations, but doesnt guarantee a correct
solution
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The Representative Heuristic
Definition: a judgment rule in which anestimate of probability or likelihood of anevent is determined by one of two
features: How similar the event is to the population of
events it came from, or
Whether the event seems similar to the
process that produced it
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Examples
A town has 2 hospitals. In 1, about 45 babiesare born each day, and only 15 are born in theother each day. On the average 50% of allbabies are boys. Though not necessarily on
every day. Across 1 year the hospitals recordedthe number of days on which 60% or more of thebabies born were males.
Which hospital had more of these days or werethey have the same number of these days?
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Example 2
You flip a coin 6 times. Given that flippinga fair coin is random ( a 50 -50 chance ora head or tail). Which of the following
outcomes is most likely or probable? A. HHTHTT
B. HHHTTT
Both are equally likely the probability is
same on each toss.
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Example 3the use of stereotypes
There are 100 people in a room, 70 of them are lawyers, 30are engineers.
Bill is randomly selected from this room. What is theprobability he is a lawyer?
Dick is a 30-year-old man. He is married with no children.A man of high ability and high motivation he promises to bevery successful. He is well liked by his colleagues.
Jack is 45-years-old, and married with 4 children. He tendsto be conservative, careful, and ambitious. He shows littleinterest in political and social interests, and enjoyscarpentry, sailing, and mathematical puzzles.
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Ignoring Base Rates
Why are more graduates first-born than second-born?
Why do more hotel fires start on the 1stten floors than thesecond ten floors
In baseball why are more runners thrown out by pitcherson 1stbase than 2ndbase?
Frank is a meek and quiet man whose only hobby is playingchess. He was near the top of his college class andmajored in philosophy. Is he a librarian or a business man?
Youve watched a coin toss come up heads 5 times in arow. If you bet $100 on the next toss, would you chooseheads or tails?
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Availability Heuristic
A judgment rule in which ones estimatesare influenced by the ease with whichrelevant examples can be remembered
General world knowledge Are there more words in the English language
that begin with R or have an R as the 3rdletter?
GM sells more Chevrolets than Cadillacs. Forevery Cadillac it sells how many Chevroletsdoes it sell?
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Other availability heuristic biases
Familiarity Bias Tversky and Kahneman(1973)
Subjects given list of 39 names, 19 womens
names and 20 names of men Group 1 asked to recall all the names on the
list; group 2 asked to determine if the list hadmore womens names or mens names
Salience and vividness biases
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Simulation heuristic
A judgment rule that involves a mentalconstruction or imagining of outcomes, aforecasting of how some event will turn
out or how it might have turned outdifferently under another set ofcircumstances
Undoing heuristic
Hindsight bias Blaming the victim
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Blaming the victim
Paul normally leaves work at 5:30 and drivesdirectly home. One day, while following hisroutine, Paul is broadsided by a driver whoviolated a stop sign and is seriously injured.
Paul, feeling restless at work, leaves early to seea movie. He is broadsided by a driver whoviolated a stop sign and is seriously injured.
Paul receives an emergency call to return home.While driving home, Paul is broadsided by adriver who violated a stop sign and is seriouslyinjured.
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Limited knowledge as a limitation in
reasoning
People who keep pushing an elevatorbutton to make it come faster
Nave physics understanding principles ofmotion
Limitations in processing resources What is the answer to 8X7X6X5X4X3X2X1
What is the answer to 1X2X3X4X5X6X7X8
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Group decision making
3 frequent errors
Group think
Incremental-decision making
Content error
l f i i
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Development of reasoning in young
adults
Relativistic reasoning
Dialectic reasoning
Systematic reasoning