Deduction and Induction
Because deduction rhymes with reduction,
you can easily remember that in deduction, you start with a set of
possibilities and reduce it until a smaller subset remains.
For example, a murder mystery is an exercise in deduction. Typically,
the detective begins with a set of possible suspects — for example, the butler,
the maid, the business partner, and the widow. By the end of the story, he or
she has reduced this set to only one person — for example, "The victim
died in the bathtub but was moved to the bed. But, neither woman could have
lifted the body, nor could the butler with his war wound. Therefore, the
business partner must have committed the crime."
Other example
- Deduction
- All men are mortal.
Socrates is a man. Therefore, Socrates is a mortal.
- Every action God has ever done
has been good. God made the world. Making the world was good.
- The book is on the table.
The table is on the floor. Therefore, the book is above the floor.
Induction begins
with the same two letters as the word increase, which can help you
remember that in induction, you start with a limited number of observations
and increase that number by generalizing.
For example, suppose you spend the weekend in a small town and
the first five people you meet are friendly, so you inductively conclude the
following: "Everybody here is so nice." In other words, you started
with a small set of examples and you increased it to include a larger set.
Other example
- Induction:
- Each book I have seen in the
library is more than a year old. All the books in the library are
over a year old.
- It might be
that all the books in the library are more than a year old. But it
is not necessarily so since we do not know if the first statement means
that I have seen every book in the library. If I have not seen
every book in the library, and might be that there are books that are
less than a year old.
In deduction, the
conclusion logically follows from the premises; it is a necessary conclusion
and is true. In induction, the conclusion "probably" follows the
premises and is not necessarily true.
Casual
Research with Example
Causal research falls under
the category of conclusive research, because of its attempt to reveal a cause
and effect relationship between two variables. Like descriptive research, this form
of research attempts to prove an idea put forward by an individual or
organization. However, it significantly differs on both its methods and its
purpose. Where descriptive research is broad in scope, attempting to better
define any opinion, attitude, or behaviour held by a particular group, causal
research will have only two objectives:
1. Understanding which variables are the cause, and
which variables are the effect.
For example,
let’s say a city council wanted to reduce car accidents on their streets. They
might find through preliminary descriptive and exploratory research that both
accidents and road rage have been steadily increasing over the past 5 years.
Instead of automatically assuming that road rage is the cause of these
accidents, it would be important to measure whether the opposite could be true.
Maybe road rage increases in light of more accidents due to lane closures and
increased traffic. It could also be the case of the old adage ‘correlation does
not guarantee causation.’ Maybe both are increasing due to another reason like
construction, lack of proper traffic controls, or an influx of new drivers.
The following are examples of research objectives for
causal research design:
§
To assess the impacts of foreign direct
investment on the levels of economic growth in Taiwan
§
To analyse the effects of re-branding
initiatives on the levels of customer loyalty
§
To identify the nature of impact of work
process re-engineering on the levels of employee motivation.
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