14. Variable
Is something that can take
more than one value and
values can be words or
numbers.
The most common variables
are age, sex, gender,
education, income , marital
status and occupation.
15. Variable
Is a measurable
characteristic that varies. It
may change from group to
group, person to person or
within one person over
time.
16. Variable
Refers to a characteristic, or
attribute of an individual or an
organization that can be
measured or observed and
that varies among the people
or organization being studied.
17. Nature of Variables
1. Nominal Variables represent
categories that cannot be ordered
in any particular way. Examples
are: biological sex (males vs.
females), political affiliation ,
basketball fan affiliation, etc.
18. Nature of Variables
2. Ordinal Variables represent
categories that can be ordered from
greatest to smallest. Examples of
ordinal variable include education
level (freshmen, sophomore, Grade
XI, income brackets. Etc.)
19. Nature of Variables
3. Interval Variables have values that
lie along an evenly dispersed range
or numbers. Examples of interval
data include temperature, a person’s
net worth (how much money, etc.)
20. Nature of Variables
4. Ratio Variables have values that
lie along an evenly dispersed range
or numbers when there is an
absolute zero as opposed to net
worth , which can have a negative
debt-to-income ratio-level variable.
That is, you cannot have income or
some positive amount of income.
21. Major Kinds of Variables
1. Independent Variables
2. Dependent Variables
3. Intervening Variables
4. Control Variables
5. Confounding Variables
23. 1. Independent
Variables
those that probably cause,
influence, or affect outcomes.
They are invariably called
treatment, manipulated,
antecedent or predictor
variables.
24. Independent Variables
Independent Variables stand alone and
they are not changed by the other
variables you are trying to measure.
Examples of independent variables are
age, gender, what people eat, how much
time they spend using gadgets, how
much TV they watch or how much time
youngsters spend on computer games
25. There can be only one independent
variable in an experiment.
This is the factor manipulated by
the researcher, and it produces one or
more results, known as dependent
variables.
Independent
Variable
26. Independent
Variable
If a scientist conducts an experiment to test
the theory that a vitamin could extend a person’s
life-expectancy, then:
The independent variable is the amount of
vitamin that is given to the subjects within the
experiment. This is controlled by the
experimenting scientist.
27. 2. Dependent
Variables
Those that depend on the independent
variables; they are the outcomes or
results of the influence of the
independent variables.
The factor that is measured or
observed; the change that is brought
about or is effected by the change in
the independent variable.
the “assumed effect” of another
28. Dependent Variables
Dependent Variables are what
researchers are interested in. They
depend other factors.
For example, a test score could be a
dependent variable because it could
change depending on several factors
such as how much time you studied,
how much sleep you got the night
before you took the test, etc.
29. If a scientist conducts an
experiment to test the theory that a
vitamin could extend a person’s life-
expectancy, then:
Dependent
Variable
The dependent variable, or the variable
being affected by the independent variable,
is the life span.
30. 3. Intervening or
Mediating Variables
“stand between” the independent
and dependent variables, and they
show the effects of the independent
variable or the dependent variable.
31. In language learning and
teaching, they are usually inside
the subject’s heads, including
various language learning
processes which the researcher
cannot observe.
32. For example, if the use of a particular
teaching technique is the independent
variable and the mastery of the
objectives is the dependent variable,
then the language learning processes
used by the subjects are intervening
variables.
33. 4. Control
Variables
• Special types of independent
variables that are measured in a
study because they potentially
influence the dependent variables.
• They may be demographic or personal
variables that need to be controlled.
34. 5. Confounding Variables
Those that are not actually
measured or observed in a study.
They exist but their influence
cannot be directly detected in a
study.
These variables may have
operated to explain the
relationship between the IV and
DV but they are not or could not
be easily assessed.
35. Examples of Variables
Phenomenon A: 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
36. Examples of Variables
Phenomenon B: Crime and violence on
streets
Examples of variables related to c and violence
in streets:
1. Number of robberies
2. Number of attempted murders
3. Number of prisoners
4. Number of crime victims
5. Number of law enforcers
6. Number of convictions
37. Examples of Variables
Phenomenon C: Poor performance of
students in college entrance examination
Examples of variables related to Poor
academic performance:
1. Entrance exam score
2. Number of hours devoted to studying
3. Number of students in the class
4. Educational attainment
5. The distance of school from home
38. All of the examples of variables can be
counted and measured using a scale.
The expected values derived from
these variables will, therefore, be in
terms of numbers, amount, category
or type.
Since quantified variables allow
statistical analysis, variables
correlations or difference can be
determined.
