Inductive Reasoning
Concepts and Principles
of
Construction
Basic Categories
Target - the category we are
interested in understanding better
 Sample - the individual or group we
already know about or understand

What is known about the sample may be the
result of observation, polling or experimentation.
Credibility of observation is always an issue. In
polling, this makes the neutrality and focus of
questions a concern. In experimentation, the issue
is experimental design.
Basic Categories
Target - the category we are
interested in understanding better
 Sample - the individual or group we
already know about or understand
 Feature in question - the property we
know about in the sample and
wonder about in the target

Using the basic categories...
Will I have a good future if I stay with Y?
Target - my future with Y (needs to be
an identifiable thing)
 Sample - whatever we already know
about Y (favorable and unfavorable)
 Feature in question - the goodness of
my future (notice that the sample's
features may not correspond
perfectly to those of the target)

Two Main Types of Inductive
Reasoning

Inductive generalization - intends a
conclusion about a class of things or
events larger than the subset that
serves as the basis for the induction
Making this type of argument work often requires
careful collection of facts, including sophisticated
methods of insuring randomness of sample.
Two Main Types of Inductive
Reasoning

Inductive generalization - intends a
conclusion about a class of things or
events larger than the subset that
serves as the basis for the induction
Example: Let's say that almost all individuals
who have worked out as managers over the past
five years belonged to the same religion. Is the
best conclusion that people who belong to this
religion are good managers?
Two Main Types of Inductive
Reasoning
Inductive generalization - intends a
conclusion about a class of things or
events larger than the subset that
serves as the basis for the induction
 Analogical argument - intends a
conclusion about a specific thing,
event, or class that is relevantly
similar to the sample

Two Main Types of Inductive
Reasoning

Analogical argument - intends a
conclusion about a specific thing,
event, or class that is relevantly
similar to the sample
Example: I've been able to trust my previous
assistants with doing the banking. So I expect I will
be able to trust my next assistant the same way.
Concerns About Samples

Is the sample representative?
The more like one another the sample and
target are, the stronger the argument.
Paying attention to this concern helps avoid
the biased sample fallacy, which (like all of the
inductive fallacies) results in an unusably weak
induction. Self-selected samples are known
problems in this regard.
Concerns About Samples

Is the sample large enough?
In general, the larger the sample, the
better.
Paying attention to this concern helps avoid
the hasty conclusion and anecdotal evidence
fallacies. These are both very common.
Focus Point: Fallacy of
Anecdotal Evidence
My roommate told me she went to a festival a few
weeks ago and got dosed with some drug that totally
knocked her out. She woke up on the way to the
hospital. Obviously, that festival is something to
avoid next year.
Does this story provide a convincing reason to
avoid that festival? Why or why not?
Focus Point: Fallacy of
Anecdotal Evidence
The sample is small, typically a
single story
 The story may be striking
 The story is treated as though it were
representative of the target
 Best use of the anecdote: to focus
attention (NOT as key premise)

Confidence and Caution
As sample size grows: confidence
increases or margin of error
decreases
 Inductions never attain 100%
confidence or 0% margin of error
 In many cases, evaluation of these
factors can be reasonable without
being mathematically precise

Mathematical Note:
Law of Large Numbers
While evaluation of factors relevant to the
strength of an induction can be reasonable
without being mathematically precise, in
cases of chance-determined repetitions, more
repetitions can be expected to bring
alternatives closer to predictable ratios. It's
not a sure thing, but it becomes ever more
likely with more repetitions.
Analogical Reasoning:
The Argument from Design
Suppose you had never seen a clock and you
find one lying on a beach. You’d assume it
had been made by an intelligent being.
Consider the Earth. It is much more
complex than a clock. So it must have been
created by an intelligent being. This, says
the argument from design, is a good reason
to think that a creator God exists. Is it?