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Reasoning and Decision Making

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Thinking Ways of thinking

Analysis – breaking down a large complex problem into smaller simpler problems

Synthesis – combining two or more concepts into a complex form

Divergent thinking – generating many ideas or possible solutions to a problem

Convergent thinking – choosing the best solution or idea of a possible many

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Categories of thinking processes Problem solving – developing a solution to a

problem situation

Judgments and decision making – involves making choices

Reasoning – drawing conclusions given specific information

Creativity – production of original thoughts and ideas

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Reasoning

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Two basic processes in reasoning 1. A process that uses existing knowledge to

reason or make decisions about new situations and information acquired during new experiences. Top-down process Errors can lead to top-down errors

2. A process that determines what new information is relevant to reasoning and decision making Confirmation bias

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Reasoning and Logic Two forms to be covered:

Syllogisms – a 3-statement logical form, the 1st two parts state premises or statements assumed to be true, and the 3rd part is a conclusion based on those premises

Conditional reasoning – a logical determination of whether evidence supports, refutes, or is irrelevant 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 of conclusion

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Conditional Reasoning An if – then statement where the if part is

the antecedent and the then statement is the consequence If the antecedent is true, the consequence is

true, or If the antecedent exists, the consequence

exists

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 not intelligent, 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 – works

opposite 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 didn’t 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 be rich

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Problem with the confirmation bias Problem is we tend to want to affirm or

deny the antecedent and ignore the consequence

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.

2nd rule: If a letter is sealed, then it has to have 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 a

correct decision

Frequently studied – decisions about physical differences Our decisions about which stimulus is the brightest ,

smallest, heaviest, etc. depends upon factors other than the physical difference between them

Example: The determination of which of 2 lights is brightest depends upon the physical difference, but also the absolute brightness of the light, the brightness of the background, and how long the lights were visible

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Distance or discrimination effect The greater the distance or difference

between two stimuli being compared, the faster the decision about their differences

Symbolic distance effect – comparisons between two symbols that represent two stimuli – 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 the

information necessary to be certain of the answer and has to use previously acquired knowledge

Primary problem: lack of knowledge and misinterpretation

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Utility Maximization Theory Humans attempt to make decisions that

provide us with the maximum gain

Subjective utility theory – modification that takes into consideration that humans are not always objective, but take consider subjective factors

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Examples of Subjective factors Satisficing – we do not always pursue the

optimal decision, but accept one that is adequate

Immediate benefit versus delayed reward – discounting 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 a

Broadway play. You buy a ticket for $100 in the morning, but when you go to the theater that evening, 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 a Broadway play and tickets cost $100. You go to the theater that evening and when you start to pay 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 correctly

guarantees a correct solution

Identify all possible solutions and try each one until you find the one that works

The use of Algorithms is not “trial and error”

Addressed in more detail in problem solving

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Heuristics A rule of thumb strategy – usually a short

cut that generally works in most situations, but doesn’t guarantee a correct solution

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The Representative Heuristic Definition: a judgment rule in which an

estimate of probability or likelihood of an event 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 babies are

born each day, and only 15 are born in the other each day. On the average 50% of all babies are boys. Though not necessarily on every day. Across 1 year the hospitals recorded the number of days on which 60% or more of the babies born were males.

Which hospital had more of these days or were they have the same number of these days?

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Example 2 You flip a coin 6 times. Given that flipping

a fair coin is random ( a 50 -50 chance or a 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 3 – the use of stereotypes There are 100 people in a room, 70 of them are lawyers, 30

are engineers.

Bill is randomly selected from this room. What is the probability 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 be very successful. He is well liked by his colleagues.

Jack is 45-years-old, and married with 4 children. He tends to be conservative, careful, and ambitious. He shows little interest in political and social interests, and enjoys carpentry, 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 1st ten floors than the

second ten floors In baseball why are more runners thrown out by pitchers on

1st base than 2nd base?

Frank is a meek and quiet man whose only hobby is playing chess. He was near the top of his college class and majored in philosophy. Is he a librarian or a business man?

You’ve watched a coin toss come up heads 5 times in a row. If you bet $100 on the next toss, would you choose heads or tails?

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Availability Heuristic A judgment rule in which one’s estimates

are influenced by the ease with which relevant 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 3rd letter?

GM sells more Chevrolets than Cadillacs. For every Cadillac it sells how many Chevrolets does it sell?

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Other availability heuristic biases Familiarity Bias – Tversky and Kahneman

(1973) Subjects given list of 39 names, 19 women’s

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 had more women’s names or men’s names

Salience and vividness biases

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Simulation heuristic A judgment rule that involves a mental

construction or imagining of outcomes, a forecasting of how some event will turn out or how it might have turned out differently under another set of circumstances Undoing heuristic Hindsight bias Blaming the victim

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Blaming the victim Paul normally leaves work at 5:30 and drives

directly home. One day, while following his routine, Paul is broadsided by a driver who violated a stop sign and is seriously injured.

Paul, feeling restless at work, leaves early to see a movie. He is broadsided by a driver who violated a stop sign and is seriously injured.

Paul receives an emergency call to return home. While driving home, Paul is broadsided by a driver who violated a stop sign and is seriously injured.

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Limited knowledge as a limitation in reasoning People who keep pushing an elevator

button to make it come faster

Naïve physics understanding principles of motion

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

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Development of reasoning in young adults Relativistic reasoning

Dialectic reasoning

Systematic reasoning