This presentation contains the lesson about the different types and kinds of variables intended to SHS teachers and students.

1. KINDS OF VARIABLES
AND THEIR USES
LESSON 3:

2. INTRODUCTION
The root word for the word variable is “vary”
or simply can change.
Variables are among the fundamentals
concepts of research, alongside with
measurement, validity, reliability, cause and
effect and theory.
Bernard (1994) defines variables as
something that can take more than one value,
and values can be words or numbers.

3. INTRODUCTION
As mentioned in our previous discussion,
variables are units of analysis, some of which
include gender, age, socio-economic status,
attitudes or behavior such as bullying, racial
discrimination, among others.
A variable specifically refers to a
characteristics, or attributes of an individual
or an organization that can be measured or
observed and that varies among the people or
organization being studied (Creswell, 2002).

4. THE NATURE OF VARIABLES AND DATA
Quantitative researchers try to count
human behaviors, that is, they attempt to
count multiple variables at the same time.
Generally speaking, variables are classified as
one of the four types: (Allen, Titsworth, Hunt,
2009).
a. Nominal variable
b. Ordinal variable
c. Interval variable
d. Ratio variable

5. THE NATURE OF VARIABLES AND DATA
Quantitative researchers try to count
human behaviors, that is, they attempt to
count multiple variables at the same time.
Generally speaking, variables are classified as
one of the four types: (Allen, Titsworth, Hunt,
2009).
a. Nominal variable
b. Ordinal variable
c. Interval variable
d. Ratio variable

6. ACTIVITY 1
Classify the following variables:
1. Blood type
2. Socio economic status
3. Eye color
4. Political affiliation
5. Educational level
6. Satisfaction rating
7. Temperature
8. pH
9. Test Score
10. Pulse
11. Weight
12. Temperature in Kelvin
13. Length
14. Dose
15. Genotype

7. THE NATURE OF VARIABLES AND DATA
1. Nominal Variables- represent
categories that cannot be ordered in
any particular way. Examples are
biological sex (e.g. males vs females),
political affiliation, basketball fan
affiliation, etc.

8. THE NATURE OF VARIABLES AND DATA
2. Ordinal Variables- represent
categories that can be ordered from
greatest to smallest. Examples of
ordinal variables include educational
level (e.g. freshman, sophomore,
Grade IX, Grade XII), income
brackets, etc.

9. THE NATURE OF VARIABLES AND DATA
3. Interval variables- have values that lie
along an evenly dispersed range of
numbers but have no true zero.
Examples of interval data include
temperature, a person’s net worth (how
much money you have when you
subtract your debt from your assets)
etc.

10. THE NATURE OF VARIABLES AND DATA
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 variables. That is, you cannot
have income or some positive amount
of income. Most scores stemming from
response to survey items are ratio-level
values because they typically cannot go
below zero.

11. KINDS OF VARIABLES
1. Independent variables- those that probably
cause, influence, or affect outcomes. They
are invariably called treatment,
manipulated, antecedent or predictor
variables.
2. Dependent variables- those that depend
on the independent variables; they are the
outcomes or results of the influence of the
independent variables.

12. KINDS OF VARIABLES
3. Interval or mediating variables- “stand
between” the independent and the
dependent variables, and they show the
effects of the independent variable on the
dependent variable.
4. Control variables- special types of
independent variables that are measured in a
study because they potentially influence the
dependent variable. Researchers use
statistical procedures (e.g. analysis of
covariance) to control these variables.

13. KINDS OF VARIABLES
5. Confounding variables- those that are not
actually measured of observed in a study.
They exist but their influence cannot be
directly detected in a study. Researchers
comment on the influence of compounding
variables after the study has been completed.
Because these variables may have operated to
explain the relationship between the
independent variable and dependent variable,
but they were not or could not be easily
assessed.