Levels of measurements nominal scale ordinal scale interval scale ratio scale

1. CHI-SQUARE
PRESENTED BY DR. HINA JALAL
HINANSARI23@@GMAIL.COM
SCALE OF
MEASUREMENT
2
EDUCATIONAL STATISTICS

2. SCALE OF MEASUREMENT
Scales of measurement is how variables are defined and
categorised. Psychologist Stanley Stevens developed the
four common scales of measurement. Each scale of
measurement has properties that determine how to properly
analyse the data.
There are four types of measurement scales: nominal,
ordinal, interval, and ratio.

3. SCALE OF MEASUREMENT
The Scales of Measurement are used to quantify
or categorize the variables and before any
research one must identify the type of the variable
under study. As different methods are used to
measure different variables

4.  The scale of measurement of variables determines the
mathematical operations of variables.
 These mathematical operations, determine which statistics can be
applied to the data.
 Interval Data: Temperature, Dates (data with an arbitrary zero Ratio
Data: Height, Weight, Age, Length (data that has an absolute zero)
Nominal Data: Male, Female, Race, Political Party (categorical data
that cannot be ranked) Ordinal Data: Degree of Satisfaction at
Restaurant (data that can be ranked).
SCALE OF MEASUREMENT

8. MEASUREMENT SCALES
 T
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9. NOMINAL SCALES
Nominal scales are naming scales that represent categories
where there is no basis for ordering the categories.
Nominal Scale Examples
diagnostic categories
gender of the participants
classification based on discrete characteristics (hair
color) group affiliation (Republican, Democrat)

10. NOMINAL SCALES EXAMPLES
 the town people live in
 a person's name
 an arbitrary identification, including identification numbers
that are arbitrary
 menu items selected
 any yes/no distinctions
 most forms of classification (species of animals or type of tree)
 location of damage in the brain

11. ORDINAL SCALES
In ordinal scales, numbers represent rank order
and indicate the order of quality or quantity, but
they do not provide an amount of quantity or
degree of quality.

12. ORDINAL SCALES EXAMPLES
 World cup teams
 any rank ordering
 class ranks
 social class categories
 order of finish in a race
 Boards result positions
 Race competitions

13. INTERVAL SCALES
 In interval scales, numbers form a continuum and provide information
about the amount of difference, but the scale lacks a true zero. The
differences between adjacent numbers are equal or known. If zero is used,
it simply serves as a reference point on the scale but does not indicate the
complete absence of the characteristic being measured.
The Fahrenheit and Celsius temperature scales are examples of interval
measurement. In those scales, 0 °F and 0 °C do not indicate an absence of
temperature

14. INTERVAL SCALES EXAMPLES
 Scores on scales that are standardized with an arbitrary mean.
 Scores on scales that are known to not have a true zero (e.g., most
temperature scales except for the Kelvin Scale)
 Scores on measures where it is not clear that zero means none of
trait (math test)
 Scores on most personality scales based on counting the
number of endorsed items

15. RATIO SCALES
Ratio scales are the easiest to understand because they
are numbers as we usually think of them. The distance
between adjacent numbers is equal on a ratio scale and
the score of zero on the ratio scale means that there is
none of whatever is being measured. Most ratio scales
are counts of things.

16. RATIO SCALES EXAMPLES
 Time to complete a task
 Number of responses given in a specified time period
 Weight, length, height of an object
 Number of children in a family
 Number of accidents detected
 Number of errors made in a specified time period

17. IMPORTANCE OF SCALES
 The most important reason for making the distinction between these
measurement scales of is that it affects the statistical procedures used
in describing and analyzing your data.
 There are dozens of examples of measures at each of these levels of
measurement, along with some exercises help in understanding of
these distinctions.

22. Dr. Hina Jalal
@AksEAina (hinansari23@gmail.com)