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RESEARCH BACKGROUND
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RESEARCH PROBLEM IDENTIFICATION
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RESEARCH PROPOSAL
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CHAPTER TWOBACKGROUND TO STUDY
VARIABLES
Variables are deduced from the word vary. A variable is any entity that can take on different
values. That is anything that can vary can be considered a variable. For example, age is a
variable because age can take different values for different people or for the same person at
different times. Country is also variable because a person's country can be assigned a value.
Variable is what you intend to study in research. Variable changes in amount, volume,
number, nature or type.
Variables aren't always 'quantitative' or numerical. For instance, in much social research and in
program evaluation, we consider the treatment or program to be made up of one or more
variables (i.e., the 'cause' can be considered a variable). An educational program can have
varying amounts of 'time on task', 'classroom settings', 'student-teacher ratios', and so on. So even
the program can be considered a variable (which can be made up of a number of sub-variables).
An attribute is a specific value on a variable. For instance, the variable sex or gender has two
attributes: male and female. Or, the variable agreement might be defined as having five
attributes:
There are also independent and dependent variables in researches. The distinction is particularly
relevant when you are investigating cause-effect relationships. The independent variable is what
you (or nature) manipulates -- a treatment or program or cause. The dependent variable is
what is affected by the independent variable -- your effects or outcomes. For example, if you
are studying the effects of a new educational program on student achievement, the program is the
independent variable and your measures of achievement are the dependent ones.
Another important distinction having to do with the term 'variable' is the distinction between an
independent and dependent variable. It took me the longest time to learn this distinction. (Of
course, I'm someone who gets confused about the signs for 'arrivals' and 'departures' at airports --
do I go to arrivals because I'm arriving at the airport or does the person I'm picking up go to
arrivals because they're arriving on the plane!). I originally thought that an independent variable
was one that would be free to vary or respond to some program or treatment, and that a
dependent variable must be one that depends on my efforts (that is, it's the treatment). But this is
entirely backwards! In fact
Finally, there are two traits of variables that should always be achieved. Each variable should be
exhaustive; it should include all possible answerable responses. For instance, if the variable is
"religion" and the only options are "Protestant", "Jewish", and "Muslim", there are quite a few
religions I can think of that haven't been included. The list does not exhaust all possibilities. On
the other hand, if you exhaust all the possibilities with some variables -- religion being one of
them -- you would simply have too many responses. The way to deal with this is to explicitly list
the most common attributes and then use a general category like "Other" to account for all
RESEARCH METHODS CHAPTER 2 RESEARCH BACKGROUND PREPARED BY MR. ANTONY AMBIA 1
, remaining ones. In addition to being exhaustive, the attributes of a variable should be mutually
exclusive; no respondent should be able to have two attributes simultaneously. While this might
seem obvious, it is often rather tricky in practice.
(Mutually exclusive means they cannot both be true (occur). A single coin toss, can either
be head or tail). For instance, you might be tempted to represent the variable "Employment
Status" with the two attributes "employed" and "unemployed." But these attributes are not
necessarily mutually exclusive -- a person who is looking for a second job while employed
would be able to check both attributes! But don't we often use questions on surveys that ask the
respondent to "check all that apply" and then list a series of categories? Yes, we do, but
technically speaking, each of the categories in a question like that is its own variable and is
treated dichotomously as either "checked" or "unchecked", attributes that are mutually exclusive.
Independent Variables (IV) & Dependent Variables (DV)
In an experiment, the independent variable is the variable that is varied or manipulated by the
researcher, and the dependent variable is the response that is measured.
An independent variable is the presumed cause, whereas the dependent variable is the presumed
effect.
The Independent Variable is the antecedent, whereas the Dependent Variable is the consequent.
.For example in a Phenomenon: climate change
Examples of variables related to climate change:
1. Sea level
2. Temperature
3. The amount of carbon emission
4. The amount of rainfall
Phenomenon: poor performance of students in college entrance exams
Examples of variables related to poor academic performance:
1. Entrance exam score
2. Number of hours devoted to studying
3. Student-teacher ratio
4. Number of students in the class
5. Educational attainment of teachers
6. Teaching style
7. The distance of school from home
8. Number of hours devoted by parents in providing tutorial support
DIFFERENCES BETWEEN DEPENDENT AND INDEPENDENT VARIABLES
INDEPENDENT DEPENDENT
1 Intentionally manipulated Intentionally left alone
2 It could be controlled It could be measured
3 It vary at known rate It vary at unknown rate
4 It is a presumed cause or possible cause It is the effect or presumed result
RESEARCH METHODS CHAPTER 2 RESEARCH BACKGROUND PREPARED BY MR. ANTONY AMBIA 2
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