26 Research Methodology

Unit 3 - Measurement and scaling techniques

Notes
Structure
3.1 Overview
3.2 Measurement and Scaling technique
3.3 Levels of measurement scale
3.4 Types of scaling technique
3.5 Selection of appropriate scaling technique
3.6 Summary

Objectives
 Explain the concepts of measurement and scaling
 Discuss four levels of measurement scales
 Classify and discuss different scaling techniques

3.1 Introduction
As we discussed earlier, the 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 respondent’s feelings, attitudes, opinions, etc. in some measurable
form. For example, a bank manager may be interested in knowing the opinion of the
customers about the services provided by the bank. Similarly, a fast food company having a
network in a city may be interested in assessing the quality and service provided by them.
As a researcher you may be interested in knowing the attitude of the people towards the
government announcement of a metro rail in Delhi. In this unit we will discuss the issues
related to measurement, different levels of measurement scales, and various types of
scaling techniques and also selection of an appropriate scaling technique.

3.2 Measurment and Scaling

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 respondent’s, characteristics are feelings, attitudes, opinions etc.
For example, you may assign ‘1’ for Male and ‘2’ for Female respondents. In response to
a question on whether he/she is using the ATM provided by a particular bank branch, the
respondent may say ‘yes’ or ‘no’. You may wish to assign the number ‘1’ for the response
yes and ‘2’ for the response no. We assign numbers to these characteristics for two reasons.
First, the numbers facilitate further statistical analysis of data obtained.

Second, numbers facilitate the communication of measurement rules and results.

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.

Scaling: Scaling is the assignment of objects to numbers or semantics according to

a rule. In scaling, the objects are text statements, usually statements of attitude, opinion,

Amity Directorate of Distance & Online Education

Research Methodology 27
or feeling. For example, consider a scale locating customers of a bank according to the
characteristic “agreement to the satisfactory quality of service provided by the branch”. Each
Notes
customer interviewed may respond with a semantic like ‘strongly agree’, or ‘somewhat agree’,
or ‘somewhat disagree’, or ‘strongly disagree’. We may even assign each of the responses
a number. For example, we may assign strongly agree as ‘1’, agree as ‘2’ disagree as ‘3’,
and strongly disagree as ‘4’. Therefore, each of the respondents may assign 1, 2, 3 or 4.

3.3 Levels of Measurement Scale

The level of measurement refers to the relationship among the values that are assigned
to the attributes, feelings or opinions for a variable. For example, the variable ‘whether the
taste of fast food is good’ has a number of attributes, namely, very good, good, neither
good nor bad, bad and very bad. For the purpose of analyzing the results of this variable,
we may assign the values 1, 2, 3, 4 and 5 to the five attributes respectively. The level of
measurement describes the relationship among these five values. Here, we are simply
using the numbers as shorter placeholders for the lengthier text terms. We don’t mean
that higher values mean ‘more’ of something or lower values mean ‘less’ of something.
We don’t assume that ‘good’ which has a value of 2 is twice of ‘very good’ which has a
value of 1. We don’t even assume that ‘very good’ which is assigned the value ‘1’ has
more preference than ‘good’ which is assigned the value ‘2’. We simply use the values as
a shorter name for the attributes, opinions, or feelings. The assigned values

of attributes allow the researcher more scope for further processing of data and
statistical analysis.

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.

a) 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. 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 are
‘twice something or other’ than men. Nor it suggests that men are somehow ‘better’ than
women. Another example of nominal scale is to classify the respondent’s income into three
groups: the highest income as group 1. The middle income as group 2, and the low-income
as group 3. 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. In designing and developing a questionnaire, it is important that the
response categories must include all possible responses. In order to have an exhaustive
number of responses, you might have to include a category such as ‘others’, ‘uncertain’,
‘don’t know’, or ‘can’t remember’ so that the respondents will not distort their information
by forcing their responses in one of the categories provided. Also, you should be careful
and be sure that the categories provided are mutually exclusive so that they do not overlap
or get duplicated in any way.

b) 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 characteristic. 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, (that is, ‘more’ or ‘less’) but not the specific amount of differences
(that is, how much ‘more’ or ‘less’). This scale is very common in marketing, satisfaction
and attitudinal research.

Amity Directorate of Distance & Online Education

28 Research Methodology

Ordinal measurements do not provide information on how much more or less of the
characteristic various objects possess. For example, if in respect of a certain characteristic
Notes
two objects have the ranks 5 and 8 and two other objects the ranks 3 and 6, we cannot
say that the differences between the two pairs are equal. There is also no way to know
that any object has none of the characteristic being measured.

The kind of descriptive statistics that can be calculated from these data are mode,
median and percentages. For example, in the following table which shows the quality
ratings given by 600 housewives to one brand of coffee one can usefully calculate the
median and modal quality

ratings. Both are ‘2’ in this case. One can also calculate the percentages of the total
appearing in each rank. But it is meaningless to calculate a mean because the differences
between ordinals scales values are not necessarily, the same.

Quality Rating No. of respondents giving ratings

1 200
2 200
3 100
4 50
5 50

c) 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. For example, the
difference between ‘1’ and ‘2’ is equal to the difference between ‘3’ and ‘4’. Further, the
difference between ‘2’ and ‘4’ is twice the difference between ‘1’ and ‘2’. However, in an
interval scale, the zero point is arbitrary and is not true zero. This, of course, has implications
for the type of data manipulation and analysis. We can carry out on data collected in this
form. It is possible to add or subtract a constant to all of the scale values without affecting
the form of the scale but one cannot multiply or divide the values. Measuring temperature
is an example of interval scale. We cannot say 400C is twice as hot as 200C. The reason
for this is that 00C does not mean that there is no temperature, but a relative point on the
Centigrade Scale. Due to lack of an absolute zero point, the interval scale does not allow
the conclusion that 400C is twice as hot as 200C.

d) 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. Examples of ratio scales include weights, lengths and
times. In the marketing research, most counts are ratio scales. For example, the number of
customers of a bank’s ATM in the last three months is a ratio scale. This is because you can
compare this with previous three months. Ratio scales permit the researcher to compare
both differences in scores and relative magnitude of scores. 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. Most financial research that deals with
rupee values utilizes ratio scales. However, for most behavioral research, interval scales
are typically the highest form of measurement. Most statistical data analysis procedures
do not distinguish between the interval and ratio properties of the measurement scales
and it is sufficient to say that all the statistical operations that can be performed on interval
scale can also be performed on ratio scales.

With a ratio measurement, the comparison between ratios of the absolute magnitude
of the numbers becomes possible. Thus, a person weighing 100kg . is said to be twice as
Amity Directorate of Distance & Online Education
Research Methodology 29
heavy as one weighing 50kg. and a person weighing 150kg is three times as heavy. Further,
with a ratio scale we can compare intervals, rank objects according to magnitude, or use
Notes
the numbers to identify the objects. All descriptive measures and inferential techniques
are applicable to ratio-measured data.

3.4 Types of Scaling Techniques

The various types of scaling techniques used in research can be classified into two
categories: (a) comparative scales, and (b) Non-comparative scales. In comparative scaling,
the respondent is asked to compare one object with another. For example, the researcher
can ask the respondents whether they prefer brand A or brand B of a detergent. On the
other hand, in non-comparative scaling respondents need only evaluate a single object.
Their evaluation is independent of the other object which the researcher is studying.
Respondents using a non-comparative scale employ whatever rating standard seems
appropriate to them. Non-comparative techniques consist of continuous and itemized
rating scales.

Comparative Scale
a) 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 (rate
between two objects at a time) according to some criterion.

Scaling Technique

Comparative Scaling Non-Comparative

Scaling

Paired Rank Constant Q-Sort

Comparison Order Sum

Continuous Rating Scale Itemised Rating Scales

Likert Semantic Stapel

Differential

b) 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 favored and unfavored
objects, but does not reveal the distance between the objects.

c) 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.

d) 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
Amity Directorate of Distance & Online Education
30 Research Methodology
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
Notes 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.

Non-Comparative Scale
The non-comparative scaling techniques can be further divided into:

(a) Continuous Rating Scale, and (b) Itemized Rating Scale.

a) Continuous Rating Scales

It is very simple and highly useful. In continuous rating scale, the respondent’s 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.

b) 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 numbers of categories that best describes the
product, brand, company, or product attribute being rated. Itemized rating scales are widely
used in marketing research.

 Likert scale: In 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 attitudinal object.
Respondents generally choose from five alternatives (say strongly agree, agree,
neither agree nor disagree, disagree, strongly disagree).
 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. The Semantic Differential scale is used for a variety of
purposes. 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 the 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 (say, +3,
+2, +1, 0, -1, -2, -3). This scale measures how close to or how distant from the
adjective a given stimulus is perceived to be.

3.5 Selection of Appropriate Scaling Techniques

In this unit, so far, you have learnt some of the important scaling techniques that are
frequently used in attitudinal research for the measurement of attitudes. Each of these
techniques has some advantages and disadvantages. Now you may ask which technique
is more appropriate to use to measure attitudes. Virtually any technique can be used to
measure the attitudes. But at the same time all techniques are not suitable for all purposes.
As a general rule, you should use a scaling technique that will yield the highest level of
information feasible in a given situation. Also, if possible the technique should permit you
the use of a variety of statistical analysis. A number of issues decide the choice of scaling
technique. Some significant issues are:
Amity Directorate of Distance & Online Education
Research Methodology 31
1) Problem Definition and Statistical Analysis: The Choice between ranking, sorting,
or rating techniques is determined by the problem definition and the type of statistical
analysis likely to be performed. For example, ranking provides only ordinal data that limits
Notes
the use of statistical techniques.

2) The Choice between Comparative and Non-comparative Scales: Some times

it is better to use a comparative scale rather than a non comparative scale. Consider the
following example:

How satisfied you are with the brand- X detergent that you are presently using?

Completely Somewhat Neither Somewhat

Satisfied satisfied satisfied nor dissatisfied dissatisfied

Completely
dissatisfied

This is a non-comparative scale since it deals with a single concept (the brand of a
detergent). On the other hand, a comparative scale asks a respondent to rate a concept.
For example, you may ask:

Which one of the following brands of detergent you prefer?

Brand-X Brand-Y

In this example you are comparing one brand of detergent with another brand.
Therefore, in many situations, comparative scaling presents ‘the ideal situation’ as a
reference for comparison with actual situation.

3) Type of Category Labels: We have discussed different types of category labels

used in constructing measurement scales such as verbal categories and numeric
categories. Many researchers use verbal categories since they believe that these categories
are understood well by the respondents. The maturity and the education level of the
respondents influence this decision.

4) Number of Categories: While there is no single, optimal number of categories,

traditional guidelines suggest that there should be between five and nine categories. Also,
if a neutral or indifferent scale response is possible for at least some of the respondents,
an odd number of categories should be used. However, the researcher must determine
the number of meaningful positions that are best suited for a specific problem.

5) Balanced versus Unbalanced Scale: In general, the scale should be balanced

to obtain objective data.

6) Forced versus Non-forced Categories: In situations where the respondents are

expected to have no opinion, the accuracy of data may be improved by a non forced scale
that provides a ‘no opinion’ category.

3.6 Summary
The issues related to measurement, different levels of measurement scales, and
various types of scaling techniques and also selection of an appropriate scaling technique
are important to understand the research analysis and in decision making.

Measurement is the assignment of numbers or other symbols to characteristics of

objects according to set rules. Scaling involves the generation of a continuum upon which
measured objects are located. The four major primary scales of measurement are nominal,
ordinal, interval, and ratio.

Amity Directorate of Distance & Online Education

32 Research Methodology

Scaling techniques can be classified as comparative or non-comparative. Comparative

Notes scaling involves a direct comparison of stimulus objects. Comparative scales include
paired comparison, rank order, constant sum, and the Q-sort. The data obtained by these
procedures have only ordinal properties.

In non-comparative scaling, each object is scaled independently of the other objects

in the stimulus set. The resulting data are generally assumed to be interval or ratio scaled.
Non-comparative rating scales can be either continuous or itemized. The itemized rating
scales are further classified as Likert, Semantic differential, or Stapel scales.

Check Your Progress

1. Which one is the crudest and simplest measuring scale among them?
a) Nominal
b) Ordinal
c) Interval
d) Ration

2. Which one is the highest measuring scale?

a) Nominal
b) Ordinal
c) Interval
d) Ratio

3. Name two type of categories of scaling techniques used in research ?

a) comparative scales
b) Non-comparative scales.
c) Rank order
d) q-sort

4. Which scale has seven point rating scale with end points associated with bipolar labels
(such as good and bad, complex and simple) that have semantic?
a) Staple scale
b) Rating scale
c) Likert scale
d) Semantic difference scale

5. In which scaling technique the scale is independent?

a) Comparative scales
b) Non-comparative scales.
c) Rank order
d) Q-sort

6. Non-comparative scale is divided into two types?

a) Continuous Rating Scale
b) Rank order scale

Amity Directorate of Distance & Online Education

Research Methodology 33
c) Constant sum scale
d) Itemized Rating Scale Notes
7. Which 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?
a) Ratio scale
b) Interval scale
c) Ordinal scale
d) Likert scale

8__________________ is the assignment of objects to numbers or semantics according

to a rule.
a) Level of measurement scale
b) Measurement
c) Scaling
d) Ratio

9. _________________is the process of observing and recording the observations that

are collected as part of research.
a) Level of measurement scale
b) Measurement
c) Scaling
d) Ratio

10. This is a comparative scaling technique in which a respondent is presented with two
objects at a time and asked to select one object (rate between two objects at a time)
according to some criterion.
a) Rank order scale
b) Q-sort scale
c) Paired comparison
d) Constant sum

Questions &Exercises

1. What is measurement?

2. What are primary scales of measurement?

3. Describe the differences between nominal and an ordinal scale.

4. What is comparative rating scale?

5. What is semantic differential scale? For what purpose is this scale used?

6. Describe Likert Scale

7. Describe the Q-sort methodology.

Amity Directorate of Distance & Online Education

34 Research Methodology

8. What are the differences between the Stapel scale and the semantic differential?
Notes Which scale is more popular?

9. What are the major decisions involved in constructing an itemized rating scale?

10. What are the differences between the following scaling techniques, and how would
you select a particular technique?
 balanced and unbalanced scales
 forced and non-forced scales

For Further Reading:

 Paul E. Green, Donald D.Tull and Gerald Albaum: Research For Marketing
Decisions, Fifth Edition, Prentice Hall Of India
 Harper W Boyd, Ralph Westphal and Stanley F Stasch: Marketing Research-Text
and Cases, Latest Edition, Richard D Irwin, Inc.
 Naresh K. Malhotra: Marketing Research-An Applied Orientation, Third Edition,
Pearson Education Asia ( Indian edition)
 Rajendra Nargundkar: Marketing Research-- Text & Cases; Tata McGraw- Hill
publishing Company Limited.
 Marketing research: G C Beri; Tata McGraw- Hill publishing Company Limited

Amity Directorate of Distance & Online Education

Research Methodology 35
Unit 4 - Questionnaire designing
Notes
Structure
4.1 Introduction
4.2 Questionnaire Design Process
a) Information needed
b) Construction of the questionnaire
c) Content of the questionnaire
d) Types of the questions
e) Wording of the questions
f) Sequence of the questions
g) Layout of the questionnaire
h) Pre-testing of the questionnaire
i) Final draft of the questionnaire
4.3 Ethical issues related to the questionnaire
4.4 Summary

Objectives
 To understand what is questionnaire and its objectives
 To understand the various steps involved in the questionnaire designing including
content of the questionnaire, wording , sequence ,whom to ask ,what to say etc
 To consider the guidelines that must be followed at each step.
 To understand the ethical issues involved in questionnaire design

4.1 Introduction
A questionnaire is a formalized set of questions for obtaining information from
respondents. It is the basic research tool and can be described as a collection of formalized
set of questions - drawn up with the research problem in mind - used for obtaining
information from the respondents for finding solutions to the research problem.

4.2 Questionnaire Design Process

a)Information needed : Before designing a questionnaire ,one should always focus on
the type of the information needed for example whether the motive of the research is find
the consumer perception or is to study the marketing strategies of a particular company
.The questionnaire for both the cases will be different .

b )Construction of the questionnaire : the analysis of the content of the each

question results in construction of the questionnaire ; why is it been included ,types of
questions ,their sequence, their wording, the final layout of the questions and final output
in the form of the questionnaire .

c) Contents of the questionnaire: Only those questions seeking the required

information should be used. So, if we require specific information regarding a
profession, or, if we are targeting children /adults we should ask relevant questions
pertaining to adults or children as the case may be, questions may be used keeping
Amity Directorate of Distance & Online Education
36 Research Methodology

in mind the target respondents .The respondents should at least know the type and
the level of expected questions expected .Questions seeking specific details about
Notes the data and time of events should be avoided. Care must be taken in designing the
questions seeking information or personal facts such as sex, life, bad habits or status
symbol .A single question may be split into multiple questions for better response from
the respondents.

Thus, following points must be considered while deciding on the content of the
questionnaire:

1) Is the Question Necessary?

2) Are Several Questions Needed Instead of One?

Sometimes, several questions are needed to obtain the required information in an
unambiguous manner. Consider the question,

“Do you think Coca-Cola is a tasty and refreshing soft drink?” (Incorrect)

Such a question is called a double-barreled question, because two or more questions

are combined into one. To obtain the required information, two distinct questions should
be asked:

“Do you think Coca-Cola is a tasty soft drink?” and

“Do you think Coca-Cola is a refreshing soft drink?” (Correct)

3) Overcoming the inability to answer

 In situations where not all respondents are likely to be informed about the topic
of interest, filter questions that measure familiarity and past experience should be
asked before questions about the topics themselves.
 A “don’t know” option appears to reduce uninformed responses without reducing
the response rate.
How many gallons of soft drinks did you consume during the last four weeks?
(Incorrect)

How often do you consume soft drinks in a typical week? (Correct)

1. ___ Less than once a week

2. ___ 1 to 3 times per week

3. ___ 4 to 6 times per week

4. ___ 7 or more times per week

4) Overcoming Unwillingness to answer; Effort required of the Respondents

Most respondents are unwilling to devote a lot of effort to provide information. This
may be because of the following reasons:

Context
 Respondents are unwilling to respond to questions which they consider to be
inappropriate for the given context.
 The researcher should manipulate the context so that the request for information
seems appropriate.

Amity Directorate of Distance & Online Education

Research Methodology 37
Legitimate Purpose
 Explaining why the data are needed can make the request for the information
seem legitimate and increase the respondents’ willingness to answer.
Notes

Sensitive Information
 Respondents are unwilling to disclose, at least accurately, sensitive information
because this may cause embarrassment or threaten the respondent’s prestige or
self-image.
 Please list all the departments from which you purchased merchandise on your
most recent shopping trip to a department store. (Incorrect)
 In the list that follows, please check all the departments from which you purchased
merchandise on your most recent shopping trip to a department store.
1. Women’s dresses ____

2. Men’s apparel ____

3. Children’s apparel ____

4. Cosmetics ____

16. Jewelry

17. Other (please specify) ____ (Correct)

To Increase the willingness of the respondents, the following points should be

considered:
1. Place sensitive topics at the end of the questionnaire.
2. Preface the question with a statement that the behavior of interest is common.
3. Ask the question using the third-person technique phrase the question as if it
referred to other people.
4. Hide the question in a group of other questions which respondents are willing to
answer. The entire list of questions can then be asked quickly.
5. Provide response categories rather than asking for specific figures.
6. Use randomized techniques.

d ) Types of the Questions

There are basically three types of questions that are generally used in the market
surveys:

1. Open-ended questions
2. Multiple choice Questions
3. Dichotomous Questions
Open -ended questions : It requires the respondents to express freely their views/
ideas in their own words .the degree of openness varies from question to question .For
example ,the question “What do you think about the ice cream ?” gives the respondents
total freedom to talk about on any brand ,flavor etc .

Advantages:
1. It avoids persuading the respondents with a pre -stated set of response categories.

2. It is helpful for problem identification and exploratory research.

Amity Directorate of Distance & Online Education

38 Research Methodology

3. Open-ended questions provide the basis for the researcher to judge the actual
Notes values and the views of the respondents.

Disadvantages:
1. It is more time -consuming
2. The response obtained maybe so varied that it may be impossible to arrive at a
conclusion
3. Coding or categorizing the respondent’s answers is a very costly and laborious
act
Multiple Choice Questions: The questions for which we have a number of choices
as answer are called multiple choice questions. The question may be provided with two or
more options and the respondents is to select any one of them which he thinks is the best.

Advantages:
1. It is easier for both the interviewer and the respondents
2. It tends to reduce the interviewer bias and bias caused by varying levels of
respondents articulation
3. The tabulation and analysis in multiple choice questions is much simpler.

Disadvantages:
1. To develop a sound set of multiple choice questions considerable effort is required
2. The list of potential answers can cause several types of distortions in the resulting
data
3. Too many questions and choices make the questionnaire monotonous.

Dichotomous Questions:
A question having two possible responses is considered to be dichotomous.
Dichotomous questions are often used in surveys that ask for a Yes/No, True/False or
Agree/Disagree response. Often, the two alternatives of interest are supplemented by a
neutral alternative, such as “no opinion,” “don’t know,” “both,” or “none.”

 Please enter your gender

Male Female

e) Wording of Questionnaire
Question wording can be defined as the translation of the desired question content
and structure into words that the respondent can clearly and easily understand. Question
wording is the most complex, critical and difficult task in designing a questionnaire

1) Errors due to Wording:

 Item Non-Response: Error arising due to poor question wording and subsequent
low quality response from the respondent.
 Response Error: Error arising due to divergence in interpretation of the question
by the respondent and the interviewer

2) Typical Wording Issues

Define the Issues As Clearly As Possible. The issues or the objectives should be
defined as clearly as possible, for example--

 Which brand of shampoo do you use?( Issue not defined, vague)

Amity Directorate of Distance & Online Education

Research Methodology 39
 Which brand or brands of shampoos have you personally used at home during
the last one month? In case of more than one brand, please list all the brands that Notes
apply?( Issue defined, explicit)

Use ordinary words

The wording of the questions should be as simple as possible so that the respondents
can easily understand .Always avoid usage of the technical terms or the jargons

 Do you think that the distribution of soft drink is adequate? (Incorrect)

 Do you think that the soft drinks are readily available when you want to buy?
(Correct)

Use unambiguous words

Ambiguity always leads to the confusion and thus should always be avoided, for
example--

 In a typical month how often do you shop in a departmental store?

1. Never
2. Occasionally
3. Sometimes
4. Often
5. Regularly

 In a typical month how often do you shop in a departmental store?

1. Once a month
2. Twice a month
3. 3 to 5 times in a month
4. More than 5 times

In the above example we can see, in the first question the options given can be
misinterpreted by the responded as each responded can have a different meaning to the
words given like sometimes, often regularly but in the second question the options are
specific and measureable and doesn’t lead to any ambiguity or confusion.

f) Sequence of the Questionnaire

 The order in which questions are put in a questionnaire may significantly affect
the response rate
 The opening questions should be interesting, simple, and non-threatening.
 Asking questionnaires which require resondents to give personal details at the
beginning of the questionnaire is generally not recommended
 Qualifying questions should serve as the opening questions.
 Basic information should be obtained first, followed by classification, and, finally,
identification information.
 Difficult, sensitive, or complex questions should be placed late in the sequence.
 General questions should precede the specific questions.
 Questions should be asked in a logical order.
 Branching questions should be designed carefully to cover all possible
contingencies.

Amity Directorate of Distance & Online Education

40 Research Methodology

 The question being branched should be placed as close as possible to the question
causing the branching, and (2) the branching questions should be ordered so that
Notes
the respondents cannot anticipate what additional information will be required.

g) Layout of the Questionnaire

The layout of questions can also influence the answers of the respondents. Good,
simple and visually appealing layouts are a must for mail surveys, but also can be useful
in personal and telephone interviews.

Factors to consider in questionnaire layout:

 Don’t overcrowd the questionnaires
 Use margins of adequate size
 Use white space if needed to seperate sections of the questionnaire
 Keep questionnaires as brief as possible
 Use a booklet instead of stapled form
 Use good quality paper
 Ensure that the title and subtitles of the questionnaire and questionnaire sections
are carefully phrased and captures the respondents attention
 Include a privacy and confidentiality mention.

h) Pre-testing of the questionnaire

 Pretesting is a very useful method for determining whether respondents have any
difficulty understanding the questionnaire and wther the questions are ambiguous
or can lead possibly to biased answers
 Pretesting ensures that costly errors in questionnaires which are given to a large
number of respondents is avoided and that damage to the image of the researchers
is avoided
 The respondents involved in a pretest should be similar in essence to the target
respondents of the research
 Personal interviewers are often used for pretesting in order to ascertain why
questions appear ambiguos or confusing etc. to respondents, and to solicit their
comments
 Pretesting provide answers to important questions for the business researcher,
such as:
 Can the questionnaire format be followed by the interviewers?
 Does the questionnaire flow naturally and conversationally?
 Can respondents answer the questions easily?
 Which alternative forms of questions work best?

i) Final draft of the Questionnaire

After the pretesting process ,some questions can be eliminated from the questionnaire
,some close - ended questions may be changed to multiple choice questions or the
sequence may be changed .Wording may also be changed and extra questions may be
added to ensure a good questionnaire .

4.3 Ethical Issues Related to Designing the Questionnaire

Several ethical issues related to the researcher respondent relationship and the
researcher client relationship may have to be addressed in designing the questionnaire.
Amity Directorate of Distance & Online Education
Research Methodology 41
1. Respondents are volunteering their time and should not be overburdened
by soliciting too much information .the researcher should avoid overly long
Notes
questionnaires.
2. Sensitive questions deserve special attention .On one hand, candid and honest
responses are needed to generate meaningful findings .On the other hand, the
researcher should not invade respondents privacy or cause them undue stress .
3. An important researcher -client issue is piggybacking, which occurs when a
questionnaire contains questions pertaining to more than one client .this is often
done in omnibus panels that different clients can use to field their questions
.in these cases, all clients must be aware of and consent to the arrangement
.Unfortunately, it is sometimes used without the knowledge of the client which is
something unethical.
4. Finally, the researcher has the ethical responsibility of designing the questionnaire
so as to obtain the required information in an unbiased manner.

Summary
Questionnaire is one of the most important tools to collect the quantitative data. It
must translate the information needed into a set of specific questions that the respondents
can and will answer. It must motivate the respondents to respond and must also help in
reducing the errors. The designing of a questionnaire is an art .The first and the foremost
step is to analyze the information needed and the type of the interviewing method .the next
step is to decide on the content of the questionnaire. The question should overcome the
respondent’s inability and unwillingness to answer. Then comes the decision regarding
the structure of the questions .The questions can be structured or unstructured.

Determining the wording of the questions involves defining the issues, using ordinary
words, using unambiguous words and using the dual statements. Once the questions
have been worded, the order in which they will be asked should be decided. Special
considerations should be given to the opening questions, type of the information, difficult
questions, and the effect of the subsequent questions. A logical order should be maintained.

Next step is of determining the form and the layout of the questionnaire .The
questionnaire should be easy to read and well formatted. Last step is the pretesting.
Moreover, several ethical issues related to the researcher-respondent relationship and
the researcher-client relationship may have to be addressed. Use of IT can also help the
researcher in designing a sound questionnaire

Check your progress

1. Which type of questionnaire is helpful for problem identification and exploratory

research?
a) Open-ended questions
b) Multiple choice Questions
c) Dichotomous Questions
d) Close ended question

2. Which type of questionnaire tends to reduce the interviewer bias and bias caused by
varying levels of respondent’s articulation, also the simplest to analyze data?
a) Open-ended questions
b) Multiple choice Questions

Amity Directorate of Distance & Online Education

42 Research Methodology

c) Dichotomous Questions
Notes d) Close ended question

3. A question having two possible responses is considered to be______________.

a) Open-ended questions
b) Multiple choice Questions
c) Dichotomous Questions
d) Close ended question

4. _____________ is one of the most important tools to collect the quantitative data.
a) Sampling technique
b) Scaling method
c) Questionnaire
d) Experimental method

5. Before designing a questionnaire, what is the prime thing one should considered?
a) Content of the questionnaire
b) Structure of the questionnaire
c) Type of the questionnaire
d) Information needed

6. When two or more question combine together to form a question is ____________________

a) Filter questions
b) Barreled question
c) Multiple choice
d) Double-barreled question

7. Which type of questionnaire is more time consuming and very costly?

a) Open-ended questions
b) Multiple choice Questions
c) Dichotomous Questions
d) Close ended question

8. What is the most complex, critical and difficult task in designing a questionnaire
structure?
a) Sequence of questionnaire
b) Words of questionnaire
c) Layout of questionnaire
d) Pre-testing of questionnaire

9. ______________is a very useful method for determining whether respondents have

any difficulty understanding the questionnaire and wther the questions are ambiguous.
a) Sequence of questionnaire
b) Words of questionnaire
c) Layout of questionnaire

Amity Directorate of Distance & Online Education

Research Methodology 43
d) Pre-testing of questionnaire
Notes
10. Which is most important factor to be considered in questionnaire layout?
a) Basic information should be obtained first, followed by classification, and, finally,
identification information.
b) The order in which questions are put in a questionnaire may significantly affect
the response rate
c) The opening questions should be interesting, simple, and non-threatening.
d) Ensure that the title and subtitles of the questionnaire and questionnaire sections
are carefully phrased and captures the respondents attention

Questions &Exercises

1. How will you determine the type of questions to be used in preparing the questionnaire?

2. What are the advantages and disadvantages of the open-ended questions?

3. What are the common mistakes made in the construction of the questionnaire? Explain
how that can be avoided?

4. How will you decide the content of the individual questions?

5. Develop a questionnaire for determining how the students select the restaurants. Use
the randomized sampling technique.

6. Design an open-ended question to determine whether households engage in gardening

also develop a multiple-choice and a dichotomous question to obtain the same
information .which form is most desirable?

7. Formulate five questions that ask respondents to provide generalizations or estimates.

For Further Reading:

 Paul E. Green, Donald D.Tull and Gerald Albaum: Research For Marketing
Decisions, Fifth Edition, Prentice Hall Of India
 Harper W Boyd, Ralph Westphal and Stanley F Stasch: Marketing Research-Text
and Cases, Latest Edition, Richard D Irwin, Inc.
 Naresh K. Malhotra: Marketing Research-An Applied Orientation, Third Edition,
Pearson Education Asia ( Indian edition)
 Rajendra Nargundkar: Marketing Research-- Text & Cases; Tata McGraw- Hill
publishing Company Limited.
 Marketing research: G C Beri; Tata McGraw- Hill publishing Company Limited

Amity Directorate of Distance & Online Education

44 Research Methodology

Unit 5 - Sampling Technique

Notes
Structure
5.1 Overview
5.2 Sample or Census
5.3 Sampling Design Process
5.4 Classification of sampling technique
5.5 Summary

Objectives
 Differentiate a sample from census and identify the conditions that favor the use
of sample versus a census
 Sampling design Process
 Classification of sampling technique
 Description of probability and non-probability sampling

5.1 Introduction
In this chapter we will try to learn about basic concepts of sampling and various
techniques of sampling. Sample design process is very essential and important step
before execute sampling process. Classification of sampling helps us to differentiate
various sampling technique and to make them understand. Sampling is stage which is
vital for market research, without this we would not be able to start our research process.

5.2 Sample or Census

A population is the aggregate of all the elements, sharing some common set of
characteristics that comprise the universe for the purpose of the marketing research
problem.

A census involves enumeration of elements of a population or study objects. A sample

is a subgroup of the elements of the population selected for participation in the study.
Sample characteristics, called statistics, are then used to make inference about population
parameters. The inferences that link sample characteristics and population parameters
are estimation procedures and test of hypotheses.

5.3 The Sampling Design Process

The sampling design process includes five steps which are closely interrelated and
relevant to all aspects of the marketing research project, from population definition to the
presentation of the results.
Define Target Population

Determine the sampling frame

Select a sampling technique

Determine the sample size

Execute the sampling Process

Amity Directorate of Distance & Online Education
Research Methodology 45
Define Target Population
The target Population is the collection of elements or objects that possess the
information sought by the researcher and about which inference are to be made. The
Notes
target population involves translating the problem definition into a precise statement of
who should and should not be included in the sample.

An element is the object about which or from which the information is desired. A
sampling unit is an element, or a unit containing the element, that is available for selection
at some stage of the sampling process.

Determine the sampling Frame

A sampling frame is a representation of the elements of the target population. It consists
of a lot or set of directions for identifying the target population. Examples of a sampling
frame include the telephone book, an association directory listing the firms in an industry,
a mailing list purchased from commercial organization, a city directory or a map. The
researcher should recognize and treat the sampling frame error.

Select a Sampling Technique

Selecting a sampling technique involves several decision of a broader nature. The
researcher must decide whether to use a Bayesian or traditional approach, to sample with
or without replacement, and to use non probability or probability sampling.

In the Bayesian approach, the elements are selected sequentially. After each element
is added to the sample, the data are collected, sample statistics computed, and sampling
cost determined. This approach is theoretically appealing.

In sampling with replacement, an element is selected from the sampling frame and
appropriate data are obtained. Then the element is placed back in the sampling frame and
appropriate data are obtained. Then the element is placed back in the sampling frame.

In sampling without replacement, once an element is selected for inclusion in the

sample, it is removed from the sampling frame, and therefore, cannot be selected again.
The calculation of statistics is done somewhat differently for the two approaches. The most
important decision about the choice of sampling technique is whether to use probability
or non probability sampling.

Determine the Sample Size

Sample size is complex and involves several qualitative and quantitative considerations.
Important qualitative factors that should be considered in determining the sample size
include:

1. The importance of decision

2. The nature of the research
3. The number of variables
4. The nature of the analysis
5. Sample size used in similar studies
6. Incidence rates
7. Completion Rate
8. Resource constraints
The nature of the research also has an impact on the sample size. For exploratory
research designs, such as those using qualitative research, the sample size is typically
small. Sample size decision should be guided by a consideration of the resource constraints.

Amity Directorate of Distance & Online Education

46 Research Methodology

In any marketing research project, money and time are limited. Other constraints include
the availability of qualified personnel for data collection.
Notes
Execute the Sampling Process
Execution of the sampling process requires a detailed specification of how the sampling
design decision with respect to the population, sampling frame, sampling unit, sampling
technique, and sample size are to be implemented. If households are the sampling unit,
an operational definition of a household is needed.

5.4 Classification of Sampling Techniques

Sampling technique may be broadly classified as non probability and probability.

Non Probability Sampling Techniques

It relies on personal judgment of the researcher rather than chance to select sample
elements. The researcher can arbitrarily or consciously decide what elements to include
in the sample.

1. Convenience Sampling
Convenience sampling attempts to obtain a sample of convenient elements. The
selection of sampling units is left primarily to the interviewer. Often, respondents are
selected because they happen to be in the right place at the right time.

Example of convenience sampling includes:

1. Use of student, church groups, and members of social organizations,

2. Mall intercept interviews without qualifying the respondents
3. Department stores using charge account lists
4. Tear-out questionnaires include in a magazine, and
5. People on street interviews
Convenience sampling is the least expansive and least time consuming of all sampling
techniques. The sampling units are accessible, easy to measure, and cooperative.

2. Judgmental Sampling
It is form of convenience sampling in which the population elements are selected based
on the judgment of researcher. The researcher, exercising judgment or expertise, choose
the elements to be included in the sample, because they he or she believes that they are
representative of the population of interest or otherwise appropriate.

3. Quota Sampling
It may be viewed as two stages restricted judgmental sampling. The first stage consists
of developing control categories, or quotas, of population elements. To develop these
quotas, the researcher lists relevant control characteristics and determines the distribution
of these characteristics and determines the distribution of these characteristics in the target
population. The relevant control characteristics, which may include sex, age, and race,
are identified on the basis of judgment.

In the second stage, sample elements are selected based on convinces or judgment.
Once quotas have been assigned, there is considerable freedom in selecting the elements
to be included in the sample.

Amity Directorate of Distance & Online Education

Research Methodology 47
4. Snowball Sampling
In snowball sampling, an initial group of respondents is selected usually at random.
After being interviewed, these respondents are asked to identify others who belong to
Notes
target population of interest. Subsequent respondents are selected based on referrals.

This process may be carried out in waves by obtaining referrals from referrals, thus
leading to snowballing effect. Even though probability sampling is used to select the initial
respondents, the final sample is non probability sample.

Probability Sampling Techniques

Probability sampling techniques vary in terms of sampling efficiency. Sampling efficiency
is a concept that reflects a tradeoff between sampling cost and precision. Precision refers
to the level of uncertainty about the characteristics being measured. Precision is inversely
related to sampling errors but positively related to cost.

1. Simple Random Sampling:

In sampling random sampling, each element in the population has a known and
equal probability of selection. Furthermore, each possible sample of a given size has
a known and equal probability of being the sample actually selected. This implies that
every sample is drawn by a random procedure from a sampling frame. To draw a simple
random sample, the researcher first complies a sampling frame in which each element is
assigned a unique identification number. Then numbers are generated to determine which
elements to include in number.

2. Systematic Sampling

In systematic sampling, the sample is chosen by selecting a random starting point

and then picking every ith element in succession from sampling frame. The sampling
interval is determined by dividing population size N by the sample size n and rounding to
the nearest integer.

Systematic sampling is similar to SRS in that each population elements has a known
and equal probability of selection. It is less costly and easier than SRS, because random
selection is done daily basis. Moreover, the random numbers do not have to be matched
with individual elements as in SRS. This reduces the cost of sampling.

3. Stratified Sampling:

Stratified sampling is a two step process in which the population is portioned into sub
population or strata. The strata should be mutually exclusive and collectively exhaustive
in that every population element should be assigned to one and only stratum and no
population element should be omitted. A major objective of stratified sampling is to increase
precision without increase cost.

The criteria for the selection of these variables consist of homogeneity, heterogeneity,
relatedness, and cost. The elements within a stratum should be as homogeneous as
possible, but the elements in different strata should be as heterogeneous as possible.

4. Cluster Sampling:

In cluster sampling, the target population is first divided into mutually exclusive and
collectively exhaustive subpopulations or clusters. Then a random sample of cluster is
selected based on probability sampling techniques such as SRS. For each selected
cluster, either all the elements are included in the sample or sample of elements is drawn
probabilistically.

Amity Directorate of Distance & Online Education

48 Research Methodology

If all the elements in each selected cluster are included in sample the procedure is
called one-stage cluster sampling. If a sample of element is drawn probabilistically from
Notes
each selected cluster, the procedure is two stage cluster sampling. A cluster sampling can
have multiple stages, as in multistage cluster sampling.

Area sampling is a common form of cluster sampling which the clusters consist of
geographic areas such as counties, blocks.

There are two type of two stage design; one type involves SRS at the first stage as
well as the second stage. This design is called two stage cluster sampling.

Cluster
Sampling

One stage Two Satge Multisatge

Sampling Sampling Sampling

Simple Cluster Probability

Sampling proportianate
Sampling

Other Probability sampling techniques:

Sequential Sampling: A probability sampling technique in which the population
elements are sampled sequentially, data collection and analysis are done at each stage
and a decision is made as to whether additional population element should be sampled.

Double Sampling: A sampling technique in which certain population elements are

sampled twice.

5.5 Summary
Sampling is the process of making a selection of sampling elements from a defined set
of elements called a population. A population is defined as per the marketing researcher’s
objective and research questions. Usually Practical M.R. uses a multi-stage selection of
sampling units, until the respondent are selected in the final stage of sampling process.

The formulas for sample size calculation can be used as one of the inputs for deciding
on the final sample size. But other considerations that ythe researcher must look into
include-the number of cities or center used, the criticality of the various questions in the
questionnaire, cell size during the analysis stage, time and budget constraints, and other
issue based on the researcher’s experience. The important thing to remember is that it is
not completely a deterministic process, but involves several assumptions and judgments
on the part of the researcher, as detailed in the chapter.

Probability sampling techniques are those in which the researcher knows the probability
of a sampling unit getting selected in the sample. In non-probability sampling methods, no
such knowledge of the selection probability is possible. The popular probability sampling
techniques are simple random sampling, systematic sampling, stratified sampling and
cluster sampling. The non-probability techniques include quota sampling, judgment
sampling, convince sampling, and snowball sampling.
Amity Directorate of Distance & Online Education
Research Methodology 49
A sample is usually more accurate than a census of a large population due to the high
non-sampling errors that occur in doing large measurements Sampling errors are those
Notes
which occur due to the selection process, and can be estimated and controlled by using
probability sampling methods. Non sampling errors include human errors in the way of
asking questions, counting data entry or tabulation, and so on. Non sampling error can be
minimized by careful selection and training of interviewers, field control procedures and
avoiding known sources of such errors. Total error in a research is the sum of sampling
and non sampling errors and researcher should minimize total error by balancing the
sampling and non-sampling errors.

Check your progress

1. In exploratory research, the sample size is-

a) Small
b) large
c) Medium
d) Very large

2. Execution of the sampling process requires a detailed specification of how the sampling
design decision with respect to the-
a) Population
b) Sample frame
c) Sample size
d) All the above

3. “People on street” interviews, is an example of-

a) Convenience sampling
b) Judgmental sampling
c) Exploratory research
d) Quota sampling

4. In snowball sampling, an initial group of respondents is selected usually-

a) On the basis of demography
b) On the basis of psychographic mapping
c) On the basis of previous works
d) On a random basis

5. Efficiency is a concept that reflects a tradeoff between-

a) sampling cost and sampling size
b) sampling size and sampling unit
c) sampling cost and sampling technique
d) sampling cost and precision

6. Sampling errors are those which occur due to the-

a) The selection process
b) Research constraints
c) Limitations in sample

Amity Directorate of Distance & Online Education

50 Research Methodology

d) Probability technique issues

Notes 7. Human errors in the way of asking questions come under-
a) Sampling errors
b) Non sampling errors
c) Probability errors
d) Calculation errors

8. The elements within a stratum should be-

a) Homogeneous
b) Heterogeneous
c) Mixed
d) Isolated

9. In case of demographic variables, what sampling would you use?

a) Judgmental sampling
b) Snowball sampling
c) Quota sampling
d) Stratified sampling

10. Referrals play a major role in-

a) Snowball sampling
b) Quota sampling
c) Convenience sampling
d) Random sampling

Questions & Exercises

1. How can we reduce sampling error?

2. How do we ensure that a sample represents its population?

3. Difference between Sample and Census?

4. Describe stratified sampling?

5. What is sequential sampling?

6. What is the major difference between judgmental and convenience sampling?

7. Describe the sampling design process.

8. What is a sampling unit? How is it different from the population element?

9. What is the relationship between quota sampling and judgmental sampling?

10. What are the distinguishing features of simple random sampling?

11. Describe the procedure for selecting a systematic random sample.

Amity Directorate of Distance & Online Education

Research Methodology 51
12. What factors should be considered while choosing probability and non-probability
sampling?
Notes
For Further Reading:
 Paul E. Green, Donald D.Tull and Gerald Albaum: Research For Marketing
Decisions, Fifth Edition, Prentice Hall Of India
 Harper W Boyd, Ralph Westphal and Stanley F Stasch: Marketing Research-Text
and Cases, Latest Edition, Richard D Irwin, Inc.
 Naresh K. Malhotra: Marketing Research-An Applied Orientation, Third Edition,
Pearson Education Asia ( Indian edition)
 Rajendra Nargundkar: Marketing Research-- Text & Cases; Tata McGraw- Hill
publishing Company Limited.
 Marketing research: G C Beri; Tata McGraw- Hill publishing Company Limited

Amity Directorate of Distance & Online Education