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Measurement and Scaling
Issues in Attitude Measurement
Levels of Measurement Scales
Types of Scaling Techniques
# Comparative Scales
# Non-comparative Scales
Selection of an Appropriate
Scaling Technique
Key Words

The Measurement & Scaling Technique helps

us to :
explain the concepts of measurement and
discuss four levels of measurement scales,
classify and discuss different scaling
techniques, and
select an appropriate attitude
measurement scale for our research problem.

Data consists of quantitative variables, like

price, income, sales etc., and qualitative
variables like knowledge, performance ,
character etc. The qualitative information must
be converted into numerical
form for further analysis. This is possible
through measurement and scaling techniques. A
common feature of survey based research is to
have respondents feelings, attitudes, opinions,
etc. in some measurable form.

Before we proceed further it will be worthwhile to

understand the following two terms: (a)
Measurement, and (b) Scaling.

a) Measurement: Measurement is the process of

observing and recording the observations that are collected
as part of research. The recording of the observations may
be in terms of numbers or other symbols to characteristics
of objects according to certain prescribed rules. The
respondents, characteristics are feelings, attitudes,
opinions etc.
The most important aspect of measurement is the
specification of rules for assigning numbers to
characteristics. The rules for assigning numbers should be
standardized and applied uniformly. This must not change
over time or objects.
b) Scaling: Scaling is the assignment of objects to
numbers or semantics according to a rule. In scaling, the

When a researcher is interested in measuring the

attitudes, feelings or opinions of respondents
he/she should be clear about the following:
a) What is to be measured?
b) Who is to be measured?
c) The choices available in data collection

The level of measurement refers to the

relationship among the values that are assigned
to the attributes, feelings or opinions for a
Typically, there are four levels of measurement
scales or methods of assigning numbers:
(a) Nominal scale,
(b) Ordinal scale,
(c) Interval scale, and
(d) Ratio scale.

Nominal Scale is the crudest among all

measurement scales but it is also the simplest
scale. In this scale the different scores on a
measurement simply indicate different categories.
The nominal scale does not express any values or
relationships between variables.
The nominal scale is often referred to as a
categorical scale.
The assigned numbers have no arithmetic
properties and act only as labels. The only
statistical operation that can be performed on
nominal scales is a frequency count. We cannot
determine an average except mode.
For example: labeling men as 1 and women as 2
which is the most common way of labeling gender
for data recording purpose does not mean women

Ordinal Scale involves the ranking of

items along the continuum of the characteristic
being scaled. In this scale, the items are classified
according to whether they have more or less of a
The main characteristic of the ordinal scale is that
the categories have a logical or ordered
relationship. This type of scale permits the
measurement of degrees of difference, (i.e.
more or less) but not the specific amount of
differences (i.e. how much more or less). This
scale is very common
in marketing, satisfaction and attitudinal research.
Using ordinal scale data, we can perform
statistical analysis like Median and Mode, but not
the Mean.
For example, a fast food home delivery shop may

Interval Scale

is a scale in which the

numbers are used to rank attributes such that
numerically equal distances on the scale represent
equal distance in the characteristic being measured. An
interval scale contains all the information of an ordinal
scale, but it also one allows to compare the
difference/distance between attributes. Interval scales
may be either in numeric or semantic formats.
The interval scales allow the calculation of averages
like Mean, Median and Mode and dispersion like Range
and Standard Deviation.
For example, the difference between 1 and 2 is equal
the difference between 3 and 4. Further, the
difference between 2 and 4 is twice the difference
between 1 and 2.
Measuring temperature is an example of interval scale.
But, we cannot say 40C is twice as hot as 20C.

Ratio Scale is the highest level of

measurement scales. This has the properties of an
interval scale together with a fixed (absolute) zero point.
The absolute zero point allows us to construct a
meaningful ratio.
Ratio scales permit the researcher to compare both
differences in scores and relative magnitude of scores.
Examples of ratio scales include weights, lengths and
For example, the number of customers of a banks ATM
in the last
three months is a ratio scale. This is because you can
compare this with previous three months.
For example, the difference between 10 and 15 minutes
is the same as the difference between 25 and 30
minutes and 30 minutes is twice as long as 15 minutes

In comparative scaling, the respondent is

asked to compare one object with another.
The comparative scales can further be divided
into the following four types of scaling techniques:
(a)Paired Comparison Scale,
(b)Rank Order Scale,
(c)Constant Sum Scale, and
(d) Q-sort Scale.

Paired Comparison Scale:

This is a comparative scaling technique in which
a respondent is presented with two objects at a
time and asked to select one object according
to some criterion. The data obtained are ordinal
in nature.
For example, there are four types of cold drinks
- Coke, Pepsi, Sprite, and Limca. The
respondents can prefer Pepsi to Coke or Coke to
Sprite, etc.

Rank Order Scale:

This is another type of comparative scaling
technique in which respondents are
presented with several items simultaneously
and asked to rank them in the order of
priority. This is an ordinal scale that
describes the favoured and unfavoured
objects, but does not reveal the distance
between the objects.
The resultant data in rank order is ordinal
data. This yields better results when direct
comparison are required between the given
The major disadvantage of this technique is
that only ordinal data can be generated.

Constant Sum Scale:

In this scale, the respondents are asked to
allocate a constant sum of units such as points,
rupees, or chips among a set of stimulus objects
with respect to some criterion.
For example, you may wish to determine how
important the attributes of price, fragrance,
packaging, cleaning power, and lather of a
detergent are to consumers. Respondents might
be asked to divide a constant sum to indicate the
relative importance of the attributes.
The advantage of this technique is saving time.
However, main disadvantages are the
respondents may
allocate more or fewer points than those
specified. The second problem is respondents
might be confused.

Q-Sort Scale:
This is a comparative scale that uses a rank order
procedure to sort objects based on similarity with
respect to some criterion. The important characteristic
of this methodology is that it is more important to
make comparisons among different responses of a
respondent than the responses between different
respondents. Therefore, it is a comparative method of
scaling rather than an absolute rating scale. In this
method the respondent is given
statements in a large number for describing the
characteristics of a product or a large number of
brands of a product.

In non-comparative scaling respondents need

only evaluate a single object. Their
evaluation is independent of the other object
which the researcher is studying.
The non-comparative scaling techniques can
be further divided into:
(a)Continuous Rating Scale, and
(b)Itemized Rating Scale.

Continuous Rating Scales :

It is very simple and highly useful. In continuous
rating scale, the respondents rate the objects by
placing a mark at the appropriate position on a
continuous line that runs from one extreme of the
criterion variable to the other.

Example :
Question: How would you rate the TV advertisement
as a guide for buying?

Itemized Rating Scales :

Itemized rating scale is a scale having numbers or
brief descriptions associated with each category. The
categories are ordered in terms of scale position and
the respondents are required to select one of the
limited number of categories
that best describes the product, brand, company, or
product attribute being rated. Itemized rating scales
are widely used in marketing research.
Itemised rating scales is further divided into three
parts, namely
(a) Likert scale,
(b) Semantic Differential Scale, and
(c) Stapel Scale.

The itemised rating scales can be in the form of : (a)

graphic, (b) verbal, or (c) numeric as shown below :

Likert Scale:
Likert, is extremely popular for measuring attitudes,
because, the method is simple to administer. With the
Likert scale, the respondents indicate their own
attitudes by checking how strongly they agree or
disagree with carefully worded statements that range
from very positive to very negative towards the
object. Respondents generally choose from five
alternatives (say strongly agree, agree, neither agree
nor disagree, disagree, strongly disagree).
A Likert scale may include a number of items or
Disadvantage of Likert Scale is that it takes longer time
to complete than other itemised rating scales because
respondents have to read each statement.
Despite the above disadvantages, this scale has
several advantages. It is easy to construct, administer

Semantic Differential Scale:

This is a seven point rating scale with end points
associated with bipolar labels (such as good and bad,
complex and simple) that have semantic meaning. It
can be used to find whether a respondent has a
positive or negative attitude towards an object. It has
been widely used in comparing brands, products and
company images. It has also been used to develop
advertising and promotion strategies and in a new
product development study.

Staple Scale:
The Stapel scale was originally developed to measure
direction and intensity of an attitude simultaneously.
Modern versions of the Stapel scale place a single
adjective as a substitute for the Semantic differential
when it is difficult to create pairs of bipolar adjectives.
The modified Stapel scale places a single adjective in
the centre of an even number of numerical Values.

A number of issues decide the choice of scaling

technique. Some significant issues are:
1)Problem Definition and Statistical Analysis,
2)The Choice between Comparative and Noncomparative Scales,
3)Type of Category Labels,
4)Number of Categories,
5)Balanced versus Unbalanced Scale, and
6)Forced versus Non-forced Categories

There are four levels of measurements:

nominal, ordinal, interval, and ratio.
The measurement scales, commonly used in
marketing research, can be divided into two
types; comparative and non-comparative
A number of scaling techniques are available for
measurement of attitudes. There is no unique
way that you can use to select a particular
scaling technique for your research study.