Measurements and Scales

1. MEASUREMENT AND SCALING
TECHINIQUES

2. MEASUREMENT
 Measurement is defined as process of
associating numbers or symbols to
observations obtained in a research study
 These observation could be qualitative or
quantitative.
 It is difficult to measure abstract or
qualitative characteristics than
quantitative characteristics
 It is easy to measure properties like
weight ,height etc. by some standard unit
of measurement

3. Continued…
 But it is difficult to measure properties
like motivation , honesty, customer’s
perceptions, brand loyalty etc.
Example:
We can record a person’s marital status as 1
,2 , 3 or 4 depending on whether the person is
single, married , widowed or divorced. We
cannot make comparison between these
numbers but can be count each number

4. SCALE
A Scale is a tool or mechanism by which individuals are
distinguished as to how they differ from one another on
the variables of interest to our study.
Scaling involves creating a continuum upon which
measured objects are located.Consider an attitude scale
from 1 to 100. Each respondent is assigned a number
from 1 to 100,with 1 = Extremely Unfavorable, and 100
=Extremely Favorable. Measurement is the actual
assignment of a number from 1 to 100 to each
respondent.
Scaling is the process of placing the respondents on a
continuum with respect to their attitude toward
treatment.

5. Classification of
measurement scales
The most widely used classification of
measurement are :
a) Nominal Scale
b) Ordinal Scale
c) Interval Scale and
d) Ratio Scale

6. NominalScale
Nominal scale is the most elementary form of
measurement .
 It is simply a system of assigning number
symbols to elements in order to label them.
 For example , a population may be classified
as males and females. Males can be assigned
numeral as 1 and females as 2 . Members of a
labeled set can only be counted.
Mode is the only measure of central tendency
that can be applied.
 Chi – squire test is the most common test of
statistical significance

7. Ordinal Scale
Ordinal scale places elements in order.
It ranks objects or elements from one
largest to smallest or first to last.
For example: ranking of students
according to scores obtained by them.
Ordinal scale represent which is greater
and which is lesser.
Appropriate measure of central tendency
is median.
Percentile is used for measuring dispersion

8. Interval Scale
 It assumes that the measurements are made in
equal units.
 i.e. gaps between whole numbers on the scale are
equal.
 e.g. Fahrenheit and Celsius temperature scales
 an interval scale does not have a true zero. e.g. A
temperature of "zero" does not mean that there is
no temperature...it is just an arbitrary zero point.
 Permissible statistics: count/frequencies, mode,
median, mean, standard deviation

9.  Ratio scale represnts the actual amount of
variables.
Eg; measures of physical dimensions such as height,
weight ,distance etc.
 similar to interval scales except that the ratio scale
has a true zero value.
 e.g. the zero point on a centimetre scale indicates
the complete absence of length or height
 allows to compare differences between numbers.
 Permits full arithmetic operation.

10. 0
1
2
3
4
5
6
7
Examples
height, weight, age,
Length
time
Income
Market share
1.What is your annual income
before taxes?
Rs;
2. How far is your workplace
from home?
miles

11. Scale Basic
Characteristics
Common
Examples
Marketing
Examples
Nominal Numbers
identify &
classify objects of football
players
Social Security Brand nos.,
nos., numbering storetypes
Percentages,
mode
Chi-square,
binomial
test
Ordinal
relative
positions of
objects butnot
the magnitude
of differences
between them
Nos.indicate the Quality
rankings,
rankings of
teams in a
tournament
Preference
rankings,
market
position, social
class
Percentile,
median
Rank-order
correlation,
Friedman
ANOVA
Ratio Zero point is
fixed, ratios of
scale values can
be compared
Length, weight Age, sales,
income, costs
Geometric
mean,
harmonic
mean
Permissible Statistics
Descriptive Inferential
Interval Differences Temperature
between objects (Fahrenheit)
Attitudes, Range, mean,
opinions, index standard
Product-
moment
Coefficient
of variation

12. Classification ofScaling
Techniques

13. Comparative scales;
Involve the respondent directly comparing
stimulus objects.
• e.g. How does Pepsi compare with Coke on
sweetness
Noncomparative scales;
Respondent scales each stimulus object
independently of other objects
• e.g. How would you rate the sweetness of Pepsi on a
scale of 1 to 10

14. Paired ComparisonScaling
 A respondent is presented with two objects and asked to
select one according to some criterion.
 The data obtained are ordinal in nature.
 Paired comparison scaling is the most widely-used
comparative scaling technique.
 It is given by the formula,
N=[n(n - 1) /2] , where `N’ – number of judgements
` n’ – Number of stimuli or objects to be judged.
 Under the assumption of transitivity, it is possible to
convert paired comparison data to a rank order.

15.  Respondents are presented with several objects
simultaneously and asked to order or rank them
according to their choices.
 It is possible that the respondent may dislike the brand
ranked 1 in an absolute sense.
 Furthermore, rank order scaling also results in ordinal
data.
 It is easier and faster than the method of paired
comparison

16.  It is used to assess the relative
importance attached by a respondent to
the stimulus objects.
 The respondents gives certain points to
each stimulus objects out of a fixed sum
of points
 The fixed sum is usually taken as 100, but
it could be other value also.

17. 1.Continues rating or graphic rating
Respondents rate the objects by placing a
mark at the appropriate position on a line
that runs from one extreme of the criterion
variable to the other.

18. Itemized Rating Scales
The respondents are provided with a scale
that has a number or brief description
associated with each category.
The categories are ordered in terms of
scale position, and the respondents are
required to select the specified category
that best describes the object being rated.
The commonly used itemized rating scales
are the Likert, semantic differential, and
Stapel scales.

19. The Likert Scale
The Likert scale requires the respondents to indicate a degree of
agreement or disagreement with each of a series of statements
about the stimulus objects.
 The analysis can be conducted on an item-by-item basis (profile
analysis), or a total (summated) score can be calculated.
 When arriving at a total score, the categories assigned to the
negative statements by the respondents should be scored by
reversing the scale.
Response alternatives:
“strongly agree”, “agree”, “uncertain”, “disagree”, and
“strongly disagree”.
Generally use either a 5- or 7-point scale

20. Semantic Differential Scales
The semantic differential is a seven-point rating
scale with end points associated with bipolar labels
that have semantic meaning.
 The negative adjective or phrase sometimes
appears at the left side of the scale and sometimes
at the right.
 This controls the tendency of some respondents,
particularly those with very positive or very
negative attitudes, to mark the right- or left-
hand sides without reading the labels.
 Individual items on a semantic differential scale
may be scored on either a -3 to +3 or a 1 to 7
scale.

21. The Stapel scale is a unipolar rating scale with ten categories
numbered from -5 to +5, without a neutral point (zero). This
scale is usually presented vertically.
SEARS
+5 +5
+4 +4
+3 +3
+2 +2X
+1 +1
HIGH QUALITY POOR SERVICE
-1 -1
-2 -2
-3 -3
-4X -4
-5 -5
The data obtained by using a Stapel scale can be analyzed in
the same way as semantic differential data.

22. Scale Basic
Characteristics
Examples Advantages Disadvantages
Continuous
Rating
Scale
Place a mark on a
continuous line
Reaction to
TV
commercials
Easy to construct Scoring can be
cumbersome
unless
computerized
Itemized Rating Scales
Likert Scale Measurement
of attitudes
Easy to construct,
administer, and
understand
More
time-consuming
Semantic
Differential
Degrees of
agreement on a 1
(strongly disagree)
to 5 (strongly agree)
scale
Seven- point scale
with bipolar labels
Versatile Controversy as
to whether the
data are interval
Stapel
Scale
Unipolar ten-point
scale,- 5 to +5,
without a neutral
point (zero)
Brand,
product, and
company
images
Measurement
of attitudes
and images
Easy to construct,
administer over
telephone
Confusing and
difficult to apply
Basic Noncomparative Scales

23. Sources of error inmeasurement
• Respondent
• Situation
• Measurer
• instrument

24. Respondent
• Reluctant to express strong negative feelings
• May have very little knowledge but may not
admit ignorance
• Result in an interview of guesses
• Limit ability to respond accurately and fully

25. Situation
• Any condition which places strain on
interview
• Affects interviewer-respondent rapport
• Can distort responses by joining in or
merely by being present

26. Measurer
• Distort responses by rewording or reordering
questions
• Behaviour, style and looks may encourage or
discourage certain replies from respondents
• Incorrect coding
• Data-analysis stage

27. Instrument
• Defective measuring instrument
• Complex words
• Beyond comprehension
• Poor sampling

28. Techniqueof developing measurement
tools
• Four-stage process
- Concept development
- Specification of concept dimensions
- Selection of indicators
- Formation of index

29. Selection of indicators
Once the dimensions of a concept have been
specified, the researcher must develop indicators
for measuring each concept element. Indicators
are specific questions, scales, or other devices
by which respondent’s knowledge, opinion,
expectation, etc., are measured. As there is
seldom a perfect measure of a concept, the
researcher should consider several alternatives
for the purpose. The use of more than one
indicator gives stability to the scores and it also
improves their validity.

30. Concept development
The first and foremost step is that of concept
development which means that the researcher
should arrive at an understanding of the major
concepts pertaining to his study. This step of
concept development is more apparent in theoretical
studies than in the more pragmatic research, where
the fundamental concepts are often already
established.

31. Specification of concept
dimensions
The second step requires the researcher to specify
the dimensions of the concepts that he developed in
the first stage. This task may either be accomplished
by deduction i.e., by adopting a more or less intuitive
approach or by empirical correlation of the individual
dimensions with the total concept and/or the other
concepts.
For instance, one may think of several dimensions
such as product reputation, customer treatment,
corporate leadership, concern for individuals, sense
of social responsibility and so forth when one is
thinking about the image of a certain company.

32. Formation of index
The last step is that of combining the various indicators
into an index, i.e., formation of an index. When we have
several dimensions of a concept or different
measurements of a dimension, we may need to combine
them into a single index. One simple way for getting an
overall index is to provide scale values to the responses
and then sum up the corresponding scores.
Such an overall index would provide a better
measurement tool than a single indicator because of the
fact that an “individual indicator has only a probability
relation to what we really want to know.” This way we
must obtain an overall index for the various concepts
concerning the research study.