When conducting research, it is essential to define the various Types of variables. These include independent and dependent variables. Independent variables are factors that affect the research study and can be manipulated, while dependent variables are the ones that are influenced by the independent factors. The following table lists the different variables and how they relate. This table can help you understand which types to include in your research study.
Extraneous
variables:
In a research study, extraneous variables are factors that
affect the dependent variable. They introduce noise and variability and can become confounding variables that obscure the true impact of the
independent variable. As a result, researchers should identify and control
extraneous variables when possible. They can be placed through a
questionnaire or an interview. In general, extraneous variables have the
following properties:
For example, the most common extraneous variable is a person's age,
which can influence a person's performance on a test. You can eliminate this variable by giving a test to a subject early in the morning. Other
variables that affect a research study's results are the time of day and
background factors. By controlling for these variables, you can minimize the
effect of extraneous variables on your research.
Exogenous
variables:
When analyzing data in a research study, it is critical to
understand how to distinguish between endogenous and exogenous variables.
Endogenous variables can be caused by the model or by external factors, such as
a weather phenomenon. On the other hand, exogenous variables are not caused by
other variables in the model and don't determine the system's value. Here
are a few examples of exogenous variables:
In the case
of agricultural production:
In the case of agricultural production, for example, it is
possible to use endogenous variables, which are those that do not influence the
outcome of a research study. In this example, a small manufacturing plant might
increase its output, but this would not affect the price of sugar. However, a
major manufacturing plant might increase its production to a point where the price
is saturated. These variables are both endogenous and exogenous and may affect the study's results.
Explanatory
variables:
Explanatory variables can be referred to as the factors that
cause changes in the dependent variable. For example, if a person is given a
caffeine dose and their reaction time decreases, this change is called a
response variable. The dependent variable is what the researcher controls,
whereas an explanatory factor can be anything that changes the outcome. This
can include anything from the type of caffeine consumed to the social status of
the individual participating in the study.
Intervening
variables:
There are two basic types of variables
in research: independent and dependent variables. The former is easily
quantified and measurable. The latter are qualitative and cannot be directly
measured. As a result, researchers must use their knowledge of a particular
situation to identify the causal relationships between variables.
This is the most important consideration for qualitative research. If you
cannot measure an intervening variable, it is not possible to draw a meaningful
conclusion from the study.
Controlled
variables:
The use of controlled variables is essential in research. It
helps researchers determine whether their findings result from independent variables or if the results are affected by other factors.
Controlled variables make it easier to repeat a research study and
choose a direct relationship between the dependent and independent variables.
In some instances, there is no direct relationship between the two, so
researchers often need to attribute the results to confounders. By
incorporating control variables into their research, researchers can avoid this
problem.
Moderator
variables:
A moderator variable is a variable that alters a
relationship between two variables. It can influence the direction of the
relationship as well as its strength. This variable type is usually
represented by an interaction term, or product term, calculated by
multiplying the independent variable by the moderator. The example below shows
how to identify a moderator variable. Once you have determined the moderator
variable, you can calculate the relationship between X and Z.
There are several reasons for including a moderating
variable in a research study. The first is that it is an important method to
assess the impact of the survey on a certain variable. Moderating variables can influence the overall results of a study. This is because they can
reduce the effect of confounding variables in the research and reduce the
number of findings that are not representative of the entire group.
Author Bio:
Carmen Troy is a research-based content writer, who works
for Cognizantt, a globally recognized professional SEO service and Research
Prospect; an 论文和论文写作服务 Mr Carmen holds a PhD
degree in mass communication. He loves to express his views on various issues,
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