Identification of variables is an
essential step in research. Variables help researcher to design theoretical
model. They pave the way towards the research objective. Variables are various
target points in research framework. They are like buttons on Joy Stick
which cause overall situation under investigation. Having good understanding
and control over these points will help researcher to develop convincing
arguments in favor of the research objective.

Word “variable” is used to represent
something which is moving or which keeps changing. It is a component which appears
in different shapes and names. A variable may have different names depending on
the angle researcher looks at the subject. That, it may be found on
different investigating routes at the same time. For example, the “gender” can be defined as
variable from various angles in same study. In the discussion of child
performance in class the gender of teacher could be an important factor. Gender
as variable can be a factor effecting “child's performance” in the class.
Gender can be a factor which defines the degree of relationship between teacher
and student. Sometimes, researcher defines
variable from the point of view of its determinants which are present inside or
outside the model. In the
discussion of “child’s performance in class” the gender of teacher is
determined by some factors outside the model. That, the “gender” of teacher
depends on other factors which are not included in the study e.g. employment regulations about gender of teacher. In each relationship a variable may take different angles. Therefore, for a researcher, it is very important to clearly identify the
positioning and labeling of the variable. Following section will
explain various types of variables and their classification.

1.
Dependent
and Independent Variables

2.
Endogenous
and Exogenous Variable

3.
Intervening
or Mediating Variable

4.
Latent(confounding)
and Manifest Variables

5.
Quantitative
and Qualitative Variables

6.
Categorical
or Measurable Variables

7.
Continuous
and Discrete Variables

In above example, the variable “gender” is taking position of an independent variable, if performance of child in class is affected
by gender. For example, in primary school, female teachers are more effective
than the male teacher. The reason is that female has natural disposition towards
child development. Therefore, gender is a factor or independent variable for
the research of child’s performance in class. The variable “gender” will become
dependent, if we are treating “gender” of teacher as a result of the job description
of the teachers at the time of appointment. Note that
dependent variable is always considered as the objective of the research. If
our objective is to understand the reason of downfall of economic growth,
then GDP growth rate may be considered a dependent variable.

Another group of variables is known
as Intervening and mediating variable. When a relationship between two
variables is depending on the presence of some other variable then it is called
intervening variable. For example, the gender-child’s performance relationship
does not exist if teacher is not there. Therefore, the presence of teacher is
necessary for the existence of the gender-child’s performance relationship. Here
variable “availability of teacher” is an intervening variable. Similarly
sometimes, we can find some variables which exist inside the model to define
the quality of the relationship but its presence is not mandatory. For example,
the age of a teacher can play an important role in the relationship between “gender”
and “child’s performance”. Thus variable “age” is a mediating or moderating
variable, which moderates the degree of relationship. This is also called
sensitivity variable. Note that the presence of intervening variables is
mandatory for the relationship, but not for the moderating variables. The
presence of moderating variables can give more control to the researcher to
define the dependent variable.

Another angle to look into the
variables is the presence of Observed and Unobserved variables. Observed
variables are also called manifest variables. And unobserved variables are
called Latent or confounding variables. The variables which are discovered and
included into the model are called manifest variables, whereas the variables which
are influencing the relationship in the model but yet to be discovered are
called latent or confounding variables. In above example, child’s performance may affect due to some hidden factor (like income level of
child’s family), but it has not yet been discovered or identified-called Latent
or Confounding variable. But all other variables dependent or independent which
are evident and measureable in the model are called manifest variables.

Quantitative and Qualitative
variable is another classification of the variables. Quantitative variables are
measureable variable which are measured through some scale of measurement. For
example, age is quantitative variable and it is measured by an interval scale
(number of years). Whereas, gender is a
qualitative or categorical variable, as it is measured by using nominal scale. Nominal
means naming the values of variable. Qualitative variables are not measureable (
means that we cannot add two gender values to make third), rather we only count
them (that how many male and how many female gender values are there). Qualitative
variables are discrete in nature, as counts are only appeared in whole numbers.
Discrete means that variable is only assigned with some values (whole numbers
1, 2, 3, 4 …). Whereas quantitative variables mostly appear as are continuous
variables. Continuous means that variables can be assigned with any value within
certain range. For example, age of a teacher can be any value between 25 years
to 40 years. It may be 35 years and 11 months (35.11) or 26 years.

The term endogenous and exogenous is another angle to look into the variables. Endogenous variables are those variables whose values can be determined inside the model. Or in other words, the factors determined these variables are present inside the model. Exogenous variables, on the other had are those whose value is determined outside the model.

The term endogenous and exogenous is another angle to look into the variables. Endogenous variables are those variables whose values can be determined inside the model. Or in other words, the factors determined these variables are present inside the model. Exogenous variables, on the other had are those whose value is determined outside the model.

**(Author: Muhammad Azeem)**
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