variable, as opposed to a constant, is simply
anything that can vary.
If we were to study the effects of work
experience on college performance, we might look at
the grades of students who have worked prior to
starting college and the grades of students who did
not work prior to starting college.
In this study, you may notice that both
groups are students so student status remains
constant between the two groups.
You may also notice that work experience is
not the same between the two groups, therefore work
experience varies and is considered a variable. If we choose students for each group who are of similar age
or similar background, we are holding these aspects
constant and therefore, they too will not vary
within our study.
experiment has at least two types of variables:
independent and dependent.
The independent variable (IV) is often
thought of as our input variable.
It is independent of everything that occurs
during the experiment because once it is chosen it
does not change.
In our experiment on college performance, we
chose two groups at the onset, namely, those with
work experience and those without.
This variable makes up our two independent
groups and is therefore called the independent
dependent variable (DV), or outcome variable, is
dependent on our independent variable or what we
start with. In
this study, college grades would be our dependent
variable because it is dependent on work experience.
If we chose to also look at men versus women,
or older students versus younger students, then
these variables would be other independent variables
and the outcome, our dependent variable (college
grades), would be dependent on them as well.
Remember that whatever is the same between
the two groups is considered a constant because they
do not vary between groups but rather remain the
same and therefore do not affect the outcome of each
Researchers must be aware that variables
outside of the independent variable(s) may confound
or alter the results of a study.
As previously discussed, any variable that
can potentially play a role in the outcome of a
study but which is not part of the study is called a
If, for instance, we had two groups in the
above mentioned study but did not control for age
then age itself may be a confound.
Imagine comparing students with work
experience with a mean age of 40 with students
without work experience and a mean age of 18.
Could we reasonably say that work experience
caused the student to receive higher grades?
This extraneous variable can play havoc on
our results as can any intervening variable such as
motivation or attention.
Addressing confounds before they alter the
results of your study is always a wise decision.