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INDUCTIVE ARGUMENTS

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Title: INDUCTIVE ARGUMENTS


1
INDUCTIVE ARGUMENTS
  • Chapter 10

2
Inductive Arguments
  • Recall that inductive arguments are meant to show
    that, given the premises, the conclusion is
    probable.
  • Remember also, that inductive arguments aim for
    strength, not validity. The latter implies that
    the truth of the premises guarantees the truth of
    the conclusion
  • There are two primary types of inductive
    arguments
  • Analogical Arguments
  • Inductive Generalization

3
Analogical Arguments
  • In analogical arguments, the arguer generally
    draws a conclusion about a single thing by
    comparing to another, similar thing.
  • Example My friends 2006 Dodge Stratus
    overheats. Im considering buying one, but Im
    thinking that perhaps I shouldnt since it might
    also have an overheating problem.

4
Analogical Arguments - Vocabulary
  • The items being compared are called the terms of
    analogy. (Ex. the two cars)
  • The term of analogy about which we draw the
    conclusion is the target. (Ex. the car that the
    arguer considers purchasing)
  • The property (or feature) in question is the
    property attributed to the target in the
    conclusion of the argument. (Ex. overheating)

5
Analogical Arguments Contd
  • The general principle on which analogical
    arguments are based is
  • The more similar the terms of the analogy, the
    higher the probability that the conclusion is
    true.
  • So, in the previous example, the arguer could
    increase the strength of the argument, if the two
    Dodges were from the same factory, if they would
    both be driven by people with similar driving
    habits, etc

6
Inductive Generalizations
  • Inductive Generalizations
  • always have a class of things as a target
  • argues from a sample of the targeted class to the
    targeted class as a whole
  • Ex. All six peaches that I bought from my local
    grocer were mushy, so all the peaches in the
    grocers batch are probably mushy.

7
Inductive Generalizations- Vocabulary
  • Note that in the previous example, the peaches
    that the arguer bought from the store constitute
    the sample.
  • The peaches in the grocers batch constitute the
    targeted class.
  • The property in question is mushiness.

8
Inductive Generalizations Contd
  • The general principle for inductive
    generalizations is
  • The more representative the sample of an
    inductive generalization is of the target, the
    stronger the argument.
  • The sample is representative in so far as it is
    similar to the target class in all relevant
    respects.

9
Biased Samples
  • In the previous example, if all of the arguers
    peaches were picked from the bottom of the fruit
    bin, then the purchased peaches would constitute
    a biased sample.
  • A biased sample is significantly different from
    the target class in one or more relevant
    respects.
  • Arguing from a biased sample weakens the
    argument.

10
Representative Samples
  • In order to obtain representative samples, we
    should use randomly selected samples, of
    sufficient size.
  • A random selection process gives every member of
    the target class an equal chance of becoming a
    member of the sample.
  • For formal inductive arguments, a standard sample
    size between 1,000 and 1,500 is generally
    considered a reasonable sample size.

11
Inductive Generalizations contd
  • A confidence level measures the arguments
    strength. A high confidence level indicates a
    highly probable conclusion.
  • Our confidence increases
  • as the size of the sample increases,
  • as the error margin increases,
  • An error margin is a range of percentage points
    within which a conclusion is claimed to fall.
    Wide error margins make for weaker arguments.
  • Note With the same confidence level, a
    generalization from a larger sample will have a
    smaller or narrower error margin making the
    argument stronger.

12
Fallacious Inductive Reasoning
  • Two examples of fallacious inductive reasoning
    are
  • Hasty Generalization
  • Generalizing from a sample that is too small.
  • Ex. Both Harvard students Ive met have been very
    rich. Harvard must only take rich kids.
  • Biased Generalizing
  • Generalizing from a non-representative sample.
  • Ex. I surveyed 2,000 students from New York
    Citys St. Thomas Catholic School. 95 said they
    never abused drugs. So we can safely conclude
    that New York doesnt really have a teenage drug
    abuse problem.

13
Class Exercises
  • The last three cameras I bought from Roy were
    total junk. Its probably the case that all Roys
    cameras are junk.
  • 1) Name the target class and the sample.
  • 2) Name the property in question.
  • 3) If all the cameras that the arguer purchased
    from Roy happened to be Sony brand, would that
    strengthen or weaken his argument?

14
Class Exercises Contd
  • An organization randomly selected and polled
    3,000 Los Angeles residents on their abortion
    views, and from those results, the organization
    concluded that 75 of Californians 3 are
    pro-choice.
  • 4) Is the sample size sufficient?
  • 5) What is the margin of error?
  • 6)What is the target class?
  • 7) Whats wrong with the conclusion?

15
Review of Tuesdays Lesson
  • Negation Claim Truth-Table
  • P P
  • T F
  • F T

16
Review of Tuesdays Lesson contd
  • Conjunction Truth-Table
  • P Q PQ
  • T T T
  • T F F
  • F T F
  • F F F

17
Review of Tuesdays Lesson contd
  • Disjunction Truth-Table
  • P Q PvQ
  • T T T
  • T F T
  • F T T
  • F F F

18
Review of Tuesdays Lesson contd
  • Conditional Truth-Table
  • P Q P?Q
  • T T T
  • T F F
  • F T T
  • F F T

19
Review Contd
  • Remember, to determine an arguments validity,
    construct a truth-table with the claim variables,
    the premises, and the conclusion. If you can find
    any row in which all the premises are true but
    the conclusion is false, then the argument is
    invalid!
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