IT is very important to know how to measure variables

1. JOMO KENYATTA UNIVERSITY OF
AGRICULTURE AND TECHNOLOGY.
MS-TCDC.
PARTICIPANTS:
VINOLD JOHN – HD319-C003-2327/2014
MARY MNYAWI – HD319-C003-2320/2014
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TASK:- MEASUREMENT OF VARIABLES
GROUP No. three.

2. Introduction
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 A concept which can take on different
quantitative values is called a variable. As such
the concepts like weight, height, income are all
examples of variables. Qualitative phenomena
(or the attributes) are also quantified on the
basis of the presence or absence of the
concerning attribute(s). (Kothari 2004 )
 From the above definition it is evidence that
variable are thing that we measure, control or
manipulate in research.

3. Introduction continues….
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 Variables such as intelligence, motivation, and academic
achievements are concepts, constructs, or traits that
cannot be observed directly. Therefore they should be
stated in precise definitions that can be observed and
measured. E.g. “governance” may be said to consist of
transparence, accountability, resources etc. This is to
say that variables are also defined by operational and
conceptual definitions.
 Simply variable is measurable characteristic that varies.
It may change from group to group, person to person, or
even within one person over time.
 Measurement is the assignment of numerals to objects
or events according to rules.

4. Types of variables.
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 In order to conduct research, you must be able to
identify your variables. These are some of the most
common types of variables in a research project.
There are six common variable types:
1. dependent variables
2. independent variables
3. intervening variables
4. moderator variables
5. control variables
6. extraneous variables

5. Independent and Dependent variables
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 If one variable depends upon or is a
consequence of the other variable, it is
termed as a dependent variable, and the
variable that is influence to the dependent
variable is termed as an independent
variable. For instance, if we say that
height depends upon age, then height is a
dependent variable and age is an
independent variable.

6. In nutshell
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Independent variables dependent variable
EDUCATION
GENDER
AGE
COMPETENCE
EXPERIENCE
SALARY

7. Intervening variables
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 refer to abstract processes that are not directly
observable but that link the independent and
dependent variables.
Intervening variables
Independent variables Dependent
variables
TEACHING
Performance
of a studentLANGUAGE

8. Moderator variables
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 Affect the relationship between the
independent and dependent
variables by modifying the effect of
the intervening variable(s).

9. Extraneous variables
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 Independent variables that are not related to
the purpose of the study, but may affect the
dependent variable are termed as extraneous
variables. Intelligence may as well affect the
social studies achievement, but since it is not
related to the purpose of the study undertaken
by the researcher, it will be termed as an
extraneous variable. Whatever effect is noticed
on dependent variable as a result of extraneous
variable(s) is technically described as an
‘experimental error’.

10. Control variables
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 One important characteristic of a good research
design is to minimize the influence or effect of
extraneous/inappropriate variable(s). The
technical term ‘control’ is used when we design
the study minimizing the effects of extraneous
independent variables. In experimental
researches, the term ‘control’ is used to refer to
restrain/free experimental conditions.

11. How are variables measured
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 Variables are not measured at one specific level
only. whether a variable will be measured one way
or another depends very much on how it is
conceptualized and on what type of indicators have
been used during measurement. The same variable
can be measured in a various way.(Sarantakos,
2005)
 This is to say that measurement can be done in
various level.

12. Levels of measurement
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 Nominal level
 This is the simplest , and the lowest type of
measurement. When measuring using a nominal scale,
one simply names or categorizes responses. Gender,
handedness, favorite color, and religion are examples of
variables measured on a nominal scale. The essential
point about nominal scales is that they do not imply any
ordering among the responses. For example, when
classifying people according to their favorite color, there
is no sense in which green is placed "ahead of" blue.
Responses are merely categorized. Nominal scales
embody the lowest level of measurement.

13. Ordinal level
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 A researcher wishing to measure consumers'
satisfaction with their governance system might ask
them to specify their feelings as either "very
dissatisfied," "somewhat dissatisfied," "somewhat
satisfied," or "very satisfied." The items in this scale are
ordered, ranging from least to most satisfied. This is
what distinguishes ordinal from nominal scales. Unlike
nominal scales, ordinal scales allow comparisons of the
degree to which two subjects possess the dependent
variable. For example, our satisfaction ordering makes it
meaningful to assert that one person is more satisfied
than another with their governance system. Such an
assertion reflects the first person's use of a verbal label
that comes later in the list than the label chosen by the
second person.

14. Interval level
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 Interval scales are numerical scales in which
intervals have the same interpretation throughout.
As an example, consider the Fahrenheit scale of
temperature. The difference between 30 degrees
and 40 degrees represents the same temperature
difference as the difference between 80 degrees and
90 degrees. This is because each 10-degree interval
has the same physical meaning (in terms of the
kinetic energy of molecules)

15. Ratio level
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 The ratio scale of measurement is the most informative
scale. It is an interval scale with the additional property
that its zero position indicates the absence of the
quantity being measured. You can think of a ratio scale
as the three earlier scales rolled up in one. Like a
nominal scale, it provides a name or category for each
object (the numbers serve as labels). Like an ordinal
scale, the objects are ordered (in terms of the ordering
of the numbers). Like an interval scale, the same
difference at two places on the scale has the same
meaning. And in addition, the same ratio at two places
on the scale also carries the same meaning.

16. Conclusion
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 Four levels of measurement have been
identified. These levels differ in how closely
they approach the structure of the number
system we use. Understanding the level of
measurement of variables used in research is
important because the level of measurement
determines the types of statistical analyses that
can be conducted. The conclusions that can be
drawn from research depend on the statistical
analysis used.

17. APPRECIATION
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THANK YOU FOR YOUR
ATTENTION.
HAIKENYI.
MWAJEFYA INO.
ASANTENI SANA.

18. References.
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 Kothari, C. (2004). Research Methodology: Methods
and techniques. New Delh: New Age International.
 Sarantakos S. (2005). Social Research, 3rd Edition.
New York: Palgrave MacMillan.
 http://linguistics.byu.edu/faculty/henrichsenl/Resea
rchMethods/RM_2_14.html. (2014, Jun 10).
Retrieved from RESEARCH METHODS: PLANNING:
Variables: http://linguistics.byu.ed