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Decision Making and Reasoning

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The goal of human action is to seek pleasure and avoid pain; in doing so each of ... However, human decision making is more complex than even this modified ... – PowerPoint PPT presentation

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Title: Decision Making and Reasoning


1
Decision Making and Reasoning
  • Chapter 12

2
Outline
  • Judgment and Decision Making
  • Classical Decision Theory
  • Satisficing
  • Elimination by Aspects
  • Heuristics and Biases
  • Deductive Reasoning
  • Conditional Reasoning
  • Inductive Reasoning

3
1. Judgment and Decision Making
  • The goal of judgment and decision making is to
    select from among choices or to evaluate
    opportunities
  • 1. Classical Decision Theory
  • Based on the assumption or rationality
  • People make their choices so as to maximize
    something of value, whatever that something may
    be
  • Mathematical models of human decision making
  • Too restricted, does not take into account the
    psychological makeup of each individual decision
    maker

4
1. Judgment and Decision Making
  • 1. Classical Decision Theory
  • Subjective expected utility theory
  • The goal of human action is to seek pleasure and
    avoid pain in doing so each of us uses
    calculations of
  • Subjective utility based on the individuals
    judged weightings of utility, rather than on
    objective criteria
  • Subjective probability based on the
    individuals estimates of likelihood, rather than
    on objective statistical computations

5
1. Judgment and Decision Making
  • 1. Classical Decision Theory
  • This theory is based on the belief that people
    seek to reach well-reasoned decisions based on
  • Consideration of all possible known alternatives
  • Use of a maximum amount of available information
  • Careful weighing of costs and benefits and
    calculation of probability
  • A maximum degree of sound reasoning
  • However, human decision making is more complex
    than even this modified theory implies

6
1. Judgment and Decision Making
  • 2. Satisficing
  • We humans are not entirely and boundlessly
    rational in making decisions
  • Bounded rationality
  • We are rational, but within limits
  • Satisficing
  • We do not consider all possible options and then
    carefully compute which of the entire universe of
    options will maximize our gains and minimize our
    losses
  • Rather, we consider options one by one, and then
    we select an option as soon as we find one that
    is satisfactory or just good enough to meet our
    minimum level of acceptability

7
1. Judgment and Decision Making
  • 3. Elimination by Aspects
  • We sometimes use a different strategy when faced
    with far more alternatives than we feel that we
    reasonably can consider in the time we have
    available
  • Elimination by aspects
  • We focus on one aspect (attribute) of the various
    options, and we form a minimum criterion for that
    aspect
  • We then eliminate all options that do not meet
    that criterion

8
1. Judgment and Decision Making
  • 4. Heuristics and Biases
  • Amos Tversky and Daniel Kahneman
  • People may be far more likely to make decisions
    based on biases and heuristics (short-cuts) than
    earlier decision-making research has suggested
  • These mental shortcuts lighten the cognitive load
    of making decisions, but they also allow for a
    much greater chance of error

9
?
  • All the families having exactly six children in a
    particular city were surveyed. In 72 of the
    families, the exact order of births of boys and
    girls was GBGBBG (G girl B boy).
  • What is your estimate of the number of families
    surveyed in which the exact order of births is
    BGBBBB?

10
1. Judgment and Decision Making
  • 4. Heuristics and Biases
  • Representativeness
  • When we use the heuristic of representativeness,
    in which we judge the probability of an uncertain
    event according to
  • (1) how obviously it is similar to or
    representative of the population from which it is
    derived
  • (2) the degree to which it reflects the salient
    features of the process by which it is generated
  • Example on the previous slide
  • First birth order is considered to be more
    representative of the number of females and males
    in the population
  • However, either birth order is equally likely to
    occur by chance

11
?
  • Are there more words in the English language that
    begin with the letter R or that have R as their
    third letter?

12
?
  • Calculate in your head the answer to the
    following problem
  • 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1

13
?
  • Calculate in your head the answer to the
    following problem
  • 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8

14
1. Judgment and Decision Making
  • 4. Heuristics and Biases
  • Availability
  • We make judgments on the basis of how easily we
    can call to mind what we perceive as relevant
    instances of a phenomenon (e.g. words beginning
    with letter R)
  • Anchoring-and-adjustment heuristic
  • People provide a higher estimate for the first
    sequence than for the second because their
    computation for the the anchor the first few
    digits multiplied by each other renders a
    higher estimate from which they make an
    adjustment to reach a final estimate

15
1. Judgment and Decision Making
  • 4. Heuristics and Biases
  • Overconfidence
  • And individuals overvaluation of her or his own
    skills, knowledge, or judgments
  • People tend to overestimate the accuracy of their
    judgments
  • Example
  • When people were 100 confident in their answers,
    they were right only 80 of the time

16
2. Deductive Reasoning
  • Proposition
  • An assertion, which may be either true of false
  • Premise
  • Propositions about which arguments are made

17
2. Deductive Reasoning
  • 1. Conditional Reasoning
  • The reasoner must draw a conclusion based on an
    if-then proposition
  • Deductive validity
  • Does not equate with truth
  • You can reach deductively valid conclusions that
    are completely untrue with respect to the world
  • People are more likely mistakenly to accept an
    illogical argument as logical if the conclusion
    is factually true

18
2. Deductive Reasoning
  • 1. Conditional Reasoning
  • Modus ponens
  • The reasoner affirms the antecedent
  • If p then q
  • p
  • q
  • Modus tollens
  • The reasoner denies the consequent
  • If p then q
  • non q
  • non p

19
2. Deductive Reasoning
  • 1. Conditional Reasoning
  • Deductive fallacies
  • Denying the antecedent
  • Affirming the consequent
  • Rather then using formal inference rules, people
    often use pragmatic reasoning schemas

20
2. Deductive Reasoning
  • 2. Syllogistic Reasoning
  • Syllogisms
  • Are deductive arguments that involve drawing
    conclusions from two premises
  • All syllogisms comprise a major premise, a minor
    premise, and a conclusion

21
2. Deductive Reasoning
  • 2. Syllogistic Reasoning
  • Linear Syllogisms
  • The relationship among the terms is linear,
    involving a quantitative or qualitative
    comparison
  • Example
  • You are smarter than your best friend.
  • Your best friend is smarter than your roommate.
  • Which of you is the smartest?

22
2. Deductive Reasoning
  • 2. Syllogistic Reasoning
  • Categorical Syllogisms
  • Comprise of two premises and a conclusion
  • The premises state something about the category
    memberships of the terms
  • Example
  • All cognitive psychologists are pianists.
  • All pianists are athletes.
  • Therefore, all cognitive psychologists are
    athletes.

23
3. Inductive Reasoning
  • In inductive reasoning, which is based on our
    observations, reaching any logically certain
    conclusion is not possible
  • The most we can strive to reach is only a strong,
    or highly probable, conclusion
  • A key feature of inductive reasoning, which forms
    the basis of the empirical method, is that we
    cannot logically leap from saying, all observed
    instances to date of X are Y to saying,
    Therefore, all X are Y it is always possible
    that the next observed X will not be a Y

24
3. Inductive Reasoning
  • Causal inferences
  • How people make judgments about whether causes
    something else
  • Errors in inductive reasoning
  • Confirmation bias
  • Teachers often expect little of students when
    they think them low in ability
  • Causality based on correlational evidence alone
  • We fail to recognize many that many phenomena
    have multiple causes

25
3. Inductive Reasoning
  • Reasoning by analogy
  • Example
  • Fire is to asbestos as water is to
  • Vinyl
  • Air
  • Cotton
  • faucet
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