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Inductive Reasoning

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Title: Inductive Reasoning


1
Chapter 10
  • Inductive Reasoning

2
The Nature of Inductive Reasoning
  • What is an inductive argument?
  • Any argument which is not deductive!
  • I.e., any argument which does not provide a
    guarantee of the truth of the conclusion if the
    premises are true.
  • Inductive arguments are probabalistic.

3
The Nature of Inductive Reasoning
  • What else?
  • Inductive arguments are ampliative, while
    deductive arguments are non-ampliative.
  • An argument is ampliative (defn) iff there is
    information contained in the conclusion that is
    not already contained in the premises.
  • Thats the trade-off! You lose the guarantee of
    the truth of the conclusion for amplification.

4
The Nature of Inductive Reasoning
  • The logical strength of inductive arguments is
    not dependent on the form of the argument, but
    rather the content of the premises. (Its the
    opposite for deductive arguments.)

5
The Nature of Inductive Reasoning
  • However, there are 4 forms of inductive arguments
    that usually regarded as logically strong so long
    as certain conditions are met.
  • Inductive generalization
  • Statistical syllogism
  • Induction by confirmation
  • Analogical reasoning

6
Inductive Generalization
  • Has the following form
  • Z percent of observed Fs are G
  • It is probable, therefore, that Z percent of all
    Fs are G.

7
Inductive Generalization
  • E.g.
  • 60 of students at STFX who were questioned
    believe in God. It is probable, therefore, that
    60 of students at STFX believe in God.

8
Inductive Generalization
  • When assessing these arguments, ask
  • Is the sample representative?
  • Is the sample large enough?

9
Statistical Syllogism
  • Has the following form
  • Z percent of all Fs are G
  • x is an F
  • Is it probable to the degree 0.Z that x is G

10
Statistical Syllogism
  • Whats the difference between an inductive
    generalization and a statistical syllogism?
  • Inductive generalizations reason from particular
    observations to a general claim about a class.
  • Statistical syllogisms reason from a general
    claim about a class to a claim about a particular
    individual.

11
Statistical Syllogism
  • E.g.,
  • 60 of students at STFX believe in God.
  • Bob is a student at STFX.
  • Therefore, there is a .6 degree of probability
    that Bob believes in God.

12
Statistical Syllogism
  • When assessing these arguments, ask
  • Is there any additional information about x that
    has not been included in the premises?
  • E.g. Bob is President of Catholic League of
    Students (prob that he believes in God
    increases).
  • E.g., Bob is President of the Atheists for the
    Environment Society (Prob that he believes in God
    decreases).

13
Induction by Confirmation
  • Induction can be used to support a hypothesis or
    theory by providing confirming instances of that
    hypothesis or theory.
  • When we propose a theory or hypothesis, there are
    certain things that ought to be observed if it is
    actually true (or probable).
  • These are called observation statements. If we
    do observe what the theory predicts, then we have
    confirmed the theory.

14
Induction by Confirmation
  • Induction by Confirmation then has the following
    form
  • If h then o
  • o
  • It is probable that h
  • NB similar to the formal fallacy of affirming
    the consequent

15
Induction by Confirmation
  • E.g. (203)
  • If the theory of general relativity is true, then
    it follows that light rays passing near the sun
    will bend.
  • During the solar eclipse of 1919 it was observed
    that light rays passing near the sun did bend.
  • It is probable therefore that the theory of
    general relativity is true.

16
Induction by Confirmation
  • When assessing these arguments, ask
  • Is the number of confirming instances relatively
    high?
  • In general, the more confirming instances the
    better the theory.
  • Are there any disconfirming instances?
  • Any disconfirming instance refutes the theory.

17
Induction by Confirmation
  • Disconfirming instances are regarded as
    refutations of a theory because such a refutation
    takes this form
  • If h then o
  • Not-o
  • Therefore not-h
  • That is, a disconfirming instances refutes a
    theory because we are dealing with a deductively
    valid argument form Modus Tollens (denying the
    consequent).

18
Analogical Reasoning
  • Analogical reasoning works by comparing things
    which are similar (analogous) and concluding that
    properties or relations that one thing has must
    also be present in the other.

19
Analogical Reasoning
  • E.g.,
  • Last year I put some fertilizer on my
    strawberries and in the fall got about 20 per
    cent more strawberries. You should do the same
    with your strawberries, since you got the same
    kind of soil. Youll probably get more
    strawberries too.

20
Analogical Reasoning
  • Analogies compare two cases the subject case,
    and the analogue case.
  • The subject case is the case about which we are
    trying to derive a conclusion (fertilizer on your
    soil)
  • The analogue case is the case about which we are
    more familiar (fertilizer on my soil).

21
Analogical Reasoning
  • The conclusion in an analogy makes a claim about
    the subject case, and in particular states that
    the subject case will (probably) have the target
    feature.
  • The target feature (increase in strawberry
    production) is the feature that is present in the
    analogue case, and it is being concluded that it
    (probably) is in the subject case.

22
Analogical Reasoning
  • There are two kinds of analogical arguments
  • Analogical Argument by Properties
  • Analogical Argument by Relations

23
Analogical Argument by Properties
  • Analogical Argument by Properties has the
    following form
  • x has A, B, C. analogue case
  • y has A, B. subject case
  • It is probable therefore that y has C target
    feature

24
Analogical Argument by Properties
  • E.g.,
  • Canada geese are water birds that nest in Canada
    in the early spring and migrate south to warmer
    climates for the winter months. Ducks are also
    water birds that nest in Canada in early spring.
    Therefore, ducks probably migrate south for the
    winter, too.

25
Analogical Argument by Properties
  • P1 analogue case Canada geese are water birds
    that nest in Canada in the early spring and
    migrate south to warmer climates for the winter
    months.
  • P2 subject case Ducks are also water birds
    that nest in Canada in early spring.
  • Conclusion Therefore, ducks probably migrate
    south for the winter target feature, too.

26
Analogical Argument by Relations
  • Analogical Argument by Relations has the
    following form
  • x is to y analogue case as a is to b subject
    case.
  • x is R to y.
  • It is probable therefore that a is R to b target
    feature

27
Analogical Argument by Relations
  • E.g.,
  • The proposal to give clean needles to prison
    inmates to stop the spread of AIDS from the use
    of dirty needles is ridiculous. It is like
    giving bank robbers normal bullets to stop them
    from using dum-dum bullets, which are much more
    damaging to the victim.

28
Analogical Argument by Relations
  • P1 Dum-dum bullets are to normal bullets (as
    used by bank robbers) analogue case as dirty
    needles are to clean (as used by prison inmates)
    subject case.
  • P2 Although dum-dum bullets are much more
    damaging to the victim, normal bullets still kill
    their victims. Further, the role of police
    officers is to stop bank robbers, not prevent the
    harms they cause.
  • Conclusion Although dirty needles are more
    damaging to the victim (addicts are likely to get
    HIV, etc.), clean needles can be just as damaging
    (e.g., overdoses). Further, the role of prison
    officials is to stop drug use, not prevent the
    harms caused by it.

29
Analogical Reasoning
  • When assessing these arguments, ask
  • Are the analogue case and the target case
    relevantly similar?
  • The more similar the two cases are, the stronger
    the analogy.
  • Of course, everything is similar to everything
    else in some respect. You are looking for strong
    similarities.
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