Week2: Deduction_vs_Induction.pdf
They are the same, except for two graphs I put on the PDF version. You can use either version. That is, if you prefer to read the blog you do not have to download and print. However, it is a good idea to download the pdf file and archive it so that you can easily access it when you are working for the assignments later in the semester.
I will see you all next week.
IREU 150 Essential Academic Skills for International
Relations
Fall 2012
Week 2 – Induction & Deduction
Notes prepared by Eser Sekercioğlu
In scicentific research, as
in logic, we often refer to the two broad methods of reasoning as the deductive and inductive approaches. We will start with the way
deduction and induction are defined in logic, then we will discuss how the
scientific method relates to both reasoning methods.
Inductive reasoning
Common example:
Observation: All left-handed people I know are creative
Murtaza is left-handed
Generalization: Murtaza is creative.
This is the common
structure of inductive reasoning about . If all left-handed people I have seen
are creative then the next left-handed person I meet must be creative too. But,
this conclusion about Murtaza can be applied to all left handed people that I
have not met yet. So, the general form of the inductive reasoning becomes:
Observation: All left-handed people we
have tested were found to be creative
Generalization: All-left handed people are
creative.
Induction is based on
regularities in experience and observation. If we observe and/or experience
something with increasing regularity our brain tells us (even without our
conscious mind noticing it) that this observation is likely to repeat itself.
And when the observation is about a relationship between two concepts or events
then whenever we observe one of the connected parts (a left handed person) we
expect to observe the other connected part (being creative).
Inductive reasoning can be
extended to include probabilistic statements as well.
Probabilistic statements
might be about generalizations to a whole class/population, for example
Observation: 85 % of people we interviewed were right-handed
Generalization: 85 % of the population is right-handed
Or, observations can be
used to make generalizations about a single case. (this is called statistical syllogism)
Observation: 95
% of left-footed football players are also left-handed
Murtaza is a left-footed football player.
Generalization: There is a 95% chance that
Induction is a bottom-up
process. We start with gathering observations and when the regularity in our observations
reach a certain level we generalize to the population/or class of things we are
investigating. For a long time (and some philosophers still insist to believe
in this) science was thought to be inductive. Because scientist collected data,
analyzed data, made generalizations, classifications etc. many philosopher of
science pictured the scientific research process as an inductive practice.
And because of this
scientific method in general was criticized. We will discuss this a little
later but we must first turn our attention to deduction.
Deduction
Deduction uses the reverse process
as induction. In the process of
induction, you begin with some data, and then determine what general
conclusion(s) can logically be derived from those data. Whereas In the process of
deduction, you begin with some statements, called 'premises', that are assumed
to be true, you then determine what else would have to be true if the premises
are true. In logic the most often given example to deductive
reasoning is:
Premise: All men are mortal
Observation: Socrates is a man
Conclusion: Socrates is mortal
In the perfect world of
logic premises are always true or they are unquestioned. Therefore conclusions
based on deductive reasoning are also always true. Similarly in mathematics
many theorems are derived from axioms which are accepted to be true. For
example all of planar geometry (all geometry topics you studied in high school)
are derived from Euclid’s five axioms. Deduction offers absolute proof. But
everything depends on the truth of the promises. If, for example, Euclid’s
axioms were wrong all geometry would collapse. If we were to find an immortal
man, then we can no longer conclude that Socrates is mortal.
We can symbolize deduction
in logic very simply as follows:
P à Q (this reads: If P then Q)
P (P is observed)
àQ (reads: then Q. This means that Q must be observed as well)
In normal grammar: If a
condition P is satisfied then the result Q must be observed. We observe that condition
P is observed, then we must also observe Q.
Deductive arguments are
evaluated for their validity and soundness. A deductive argument can be
logically valid but not sound.
Every left-handed person is a genius.
Murtaza
is left-handed
Murtaza is a genius.
This argument is valid. If the premise that all
left-handed persons are geniuses is true than Murtaza must really be a genius.
However, we know that the premise is not true. Therefore the conclusion may or
may not be true. Therefore the argument above is not sound.
Applied to scientific
inquiry, deduction is a top-down approach. We might begin with thinking up a theory about our topic of interest. We then narrow that down
into more specific hypotheses that
we can test. We narrow down even further when we collect observations to
address the hypotheses. This ultimately leads us to be able to test the
hypotheses with specific data -- a confirmation (or not) of our original theories. In
other words, deductive reasoning works from the more general to the more
specific.
These two methods of
reasoning have a very different "feel" to them when you're conducting
research. Inductive reasoning, by its very nature, is more open-ended and
exploratory, especially at the beginning. Deductive reasoning is more narrow in
nature and is concerned with testing or confirming hypotheses. Even though a
particular study may look like it's purely deductive (e.g., an experiment
designed to test the hypothesized effects of some treatment on some outcome), most
social research involves both inductive and deductive reasoning processes at
some time in the project. In fact, it doesn't take a rocket scientist to see
that we could assemble the two graphs above into a single circular one that
continually cycles from theories down to observations and back up again to
theories. Even in the most constrained experiment, the researchers may observe
patterns in the data that lead them to develop new theories.
