ARM Module 3 advanced research methodology

Scales of Measurement & Data Processing
Types of Data Measurement Scale, Techniques of Data Scaling,
Goodness of Measurement Scales, Deciding the scale, Validating
the Scale. Data Processing: Processing and Distribution- Field Work
Validation-Tabulation-Editing-Coding-Classification and Tabulation of
Data-Presentation-Graphical Representation. Reliability and Validity:
Meaning, Types and Need. Sources of Data: Primary and
Secondary Sources-Qualitative and Quantitative Methods of Data
Collection, Constructing Questionnaire, Standardized
Questionnaire, Questionnaire Vs. Schedules.

Variables
• In research, the characteristic or phenomenon that
can be measured or classified is called a variable.
There are 4 levels of variables:

Differences in Types of Scales

Levels of Data
• Ordinal= data ordered, but distance between intervals not
always equal. E.g. Low, middle and high income, or rating a
brand of soft drink on a scale of 1-5.
• Interval= equal distance between each interval. E.g. 1,2,3.
Arbitrary zero point (ex. Fahrenheit scale for temperature -
temperature does not cease to exist at 0 degrees.
• Ratio= similar to interval scale, but has true zero point E.g.
Weight, salary ($0=$0).

Nominal Data
• Nominal/Categorical (E.g. Male or Female; Colors, Country, State, Territory,
Region) has no order.
• Nominal= categorical
• E.g. Apples and pears, gender, eye colour, ethnicity.
• Data that is classified into categories and cannot be arranged in any particular order.
• – Nominal=Categorical=Dichotomous

Ordinal Data
• 2. Ordinal (E.g. 1st, 2nd and 3rd in class ranking) ordered
• Ordinal= data ordered, but distance between intervals not
always equal. E.g. Low, middle and high income, or rating a
brand of soft drink on a scale of 1-5.

Attribute Rank
Food Quality
Prices
Menu Variety
Ambience
Service
Attribute Rank
After Sale Service
Prices
Re-Sale Value
Fuel Efficiency
Aesthetic Appeal

Interval Data
• The interval scale measurement is the next higher level of measurement.
It takes care of the limitation of the ordinal scale measurement whereas
the difference between the score on the ordinal scale does not have any
meaningful interpretation.
• Interval (E.g. Celsius and Fahrenheit) there is no absolute zero

Ratio Data
• This is the highest level of measurement.
• Ratio/ continuous (E.g. 10kgs is twice as much as 5kgs) there is a true zero point.
• All the mathematical operations can be carried out using the ratio scale data.

Comparitive Scales
• A question like ‘How do you rate Barista in comparison to
Cafe Coffee Day on quality of beverages? is an example
of Comparative rating scale. It involves the direct
comparison of stimulus objects. For eg. respondents may
be asked whether they prefer Chinese in Comparison to
Indian food.

Consider the following set of questions generally used to compare various attributes of
Domino’s Pizza and Pizza Hut.
Attributes
Variety of menu options 1 2 3 4 5 6 7 8 9 10 11
Value for money 1 2 3 4 5 6 7 8 9 10 11
Speed of service(delivery) 1 2 3 4 5 6 7 8 9 10 11
Promotional offers 1 2 3 4 5 6 7 8 9 10 11
Food Quality 1 2 3 4 5 6 7 8 9 10 11
Brand Name 1 2 3 4 5 6 7 8 9 10 11
Quality of service 1 2 3 4 5 6 7 8 9 10 11
Convenience in terms of takeaway location 1 2 3 4 5 6 7 8 9 10 11
Friendliness of sales person 1 2 3 4 5 6 7 8 9 10 11
Quality of packaging 1 2 3 4 5 6 7 8 9 10 11
Adaptation of Indian taste 1 2 3 4 5 6 7 8 9 10 11
Side/orders/appetisers 1 2 3 4 5 6 7 8 9 10 11

Paired Comparison Scales
• Here a respondent is presented with two objects and is
asked to select one according to whatever criterion he or
she wants to use.

Rank Order Scaling
• Respondents are presented with several objects
simultaneously and asked to order or rank them
according to some criterion.
• Like paired comparison, this approach is also
comparative in nature.

Constant sum rating scaling
• In constant sum rating scale, the respondents are asked
to allocate a total of 100 points between various objects
and brands. The respondents distributes the points to the
various objects in the order of his preference.
• Allocate a total of 100 points among the various schools
into which you would like to admit your child. the more
points you allocate to a school, more preferred it is to be
considered. The sum should be 100.

Q Sort Technique
• It was developed to discriminate among a large number
of objects quickly. This technique makes use of the rank
order procedure in which objects are sorted into different
piles based on their similarility with respect to certain
criterion. Suppose there are 100 statements and an
individual is asked to pile them into five groups, in such a
way, that are strongly agreed statements, then agreed
statements, then neutral, Disagree and then strongly
disagree in one pile.

• https://m.youtube.com/watch?v=bwZGV6I_OP4

Non-Comparative Scales
• The respondents do not make use of any frame of
reference before answering the questions. The resulting
data is generally assumed to be interval or ratio scale.

Graphic Rating Scale
• This is a continuous scale, in which the respondents is
asked to tick his preference on a graph.

Likert Scale
• This is a multiple item agree-disagree five point scale. The
respondents are given a certain number of items
(Statements) on which they are asked to express their
degree of agreement/disagreement. This is also called a
summated scale because the scores on individual items
can be added together to produce a total score for the
respondents. An assumption of the Likert scale is that
each of the items measures some aspect of a single
common factor, other wise the scores on the items cannot
legitimately be summed up.

Semantic Scale
• This scale is widely used to compare the images of
competing brands, companies or services. Here the
respondents is required to rate each attitude or object on
a number of five or seven point rating scales. This scale is
bounded at each end by bipolar adjectives or phrases.

Stapel Scale
• The Stapel scale is used to measure the direction and
intensity of an attitude. It may be difficult to use semantic
differential scales because of the problem in creating
bipolar adjectives. The stapel scale overcomes this
problem by using only single adjectives.
• Usually 10 categories involving numbering +5 to -5
without a neutral point and is usually presented in a
vertical form.

Goodness of Measurement Scales

Goodness of Measurement Scales
• Reliability
• Reliability indicates how consistently a scale measures a
concept or construct. Reliability is concerned with consistency,
accuracy and predictability of the scale. It refers to the extent to
which a measurement process is free from random errors.
• TEST-RETEST RELIABILITY
• In this method, repeated measurements of the same person or
group using the same scale under similar conditions are taken.
A very high correlation between the two scores indicates that
the scale is reliable.

• SPLIT HALF RELIABILITY METHOD
• This method is used in the case of multiple item scales.
Here the number of items is randomly divided into two parts
and a correlation coefficient between the two is obtained.
• A High correlation indicates that the internal consistency of
the construct leads to greater reliability.
• Another measure which is used to test the internal
consistency of a multiple item scale is the coefficient alpha
(α) commonly known as Cronbach alpha.

Validity
• The validity of a scale refers to the question whether we
are measuring what we want to measure. Validity of the
scale refers to the extent to which the measurement
process is free from both systematic and random errors.
The validity is more serious issue than reliability.
• CONTENT VALIDITY
• This is also called as face validity. It involves subjective
judgement by an expert for assessing the
appropriateness of the construct.

• CONCURRENT VALIDITY
• It is used to measure the validity of the new measuring techniques by correlating
them with the established techniques. It involves computing the correlation
coefficient of two measures of the same phenomena(for example, perception of
an airline and image of a company) which are administered at the same time.
• PREDICTIVE VALIDITY
• This involves the ability of a measured phenomena at one point of time to predict
another phenomenon at a future point of time. If the correlation coefficient
between the two is high, the initial measure is said to have a high predictive
ability. As an example, consider the use of the common admission test (CAT) to
shortlist candidates for admission to the MBA programme in a business school.
The CAT scores are supposed to predict the candidates aptitude for students
towards business education.

Sensitivity
• The sensitivity of a scale is an important measurement
concept, particularly when changes in attitudes are under
investigation. Sensitivity refers to an instruments ability to
accurately measure the variability in a concept.
• The sensitivity of the scale is generally increased by
adding more response points or by adding scale items.

Data Preparation Process
• The plan of data analysis is decided in advance before collecting the
data. Important steps of data preparation process are as follows
• Questionnaire
• Editing
• Coding
• Classification
• Tabulations
• Graphical representation
• Data Cleaning
• Data Adjusting

• The data, after collection, has to be processed and analysed in
accordance with the outline laid down for the purpose at the time of
developing the research plan.
• Processing implies 1) editing, 2) coding, 3) classification and 4)
tabulation of collected data so that they are amenable to analysis.
• The term analysis refers to the computation of certain measures along
with searching for patterns of relationship that exist among data-groups.

• Questionnaire checking
• When the data is collected through questionnaires, the first step of
data preparation process is to check the questionnaires if they are
acceptable or not.
• A questionnaire may not be acceptable if
• (i) It is incomplete partially or fully
• (ii) It is answered by a person who has inadequate knowledge or
does not qualify for the participation
• (iii) It is answered in such a way which gives the impression that
the respondent could not understand the questions.

• Field Work Validation/Questionnaire Checking
• In case the form had been translated into another language,
expert analysis to see whether the meaning of the questions in
the two measures is the same or not.
• It is essential to carry out checks during the fieldwork as well as to
ensure that the process being followed is correct. As here there is
both a time and a cost element involved, in case the ivnestigators
are erring to be corrected immediately.
• The respondent seems to have used response category for all the
questions; Eg. 3 as the answer for all in 5 point scale.

1. Editing
• Editing of data is a process of examining the collected raw data (specially in surveys) to
detect errors and omissions and to correct these when possible.
• As a matter of fact, editing involves a careful scrutiny of the completed questionnaires
and/or schedules.
• Editing is done to assure that the data are accurate, consistent with other facts gathered,
uniformly entered, as completed as possible and have been well arranged to facilitate
coding and tabulation.
• Field Editing- consists in the review of the reporting forms by the investigator for
completing what the latter has written in abbreviated and/or in illegible form at the time of
recording the respondents responses.
• Central Editing- Editing done in one place either by one or group editors.
• Editors may correct obvious errors such as an entry in the wrong place, entry recorded

Coding
•Coding refers to the process of assigning numerals or other symbols to answers
so that responses can be put into a limited number of categories or classes. Such
classes should be appropriate to the research problem under consideration.
3. Classification
•Most research studies result in a large volume of raw data which must be
reduced into homogeneous groups if we are to get meaningful relationships.
•This fact necessitates classification of data which happens to be the process of
arranging data in groups or classes on the basis of common characteristics.
•Data having a common characteristic are placed in one class and in this way the
entire data get divided into a number of groups or classes.

• Classification according to class intervals
unlike descriptive characteristics, the numericals refer to
quantitative phenomenon which can be measured
through some statistical units. Data relating to income,
production, age, weight etc come under this category.
Such data are known as statistics of variables and are
classified on the basis of class intervals.

Tabulation
• When a mass of data has been assembled, it becomes
necessary for the researcher to arrange the same in some kind
of concise and logical order.
•This procedure is referred to as tabulation. Thus, tabulation is
the process of summarising raw data and displaying the same in
compact form (i.e., in the form of statistical tables) for further
analysis.
•In a broader sense, tabulation is an orderly arrangement of
data in columns and rows.

Graphical Presentation
• Graphs help to understand the data easily. All statistical
packages, MS Excel, and openOffice.org offer a wide
range of graphs. Most common graphs are bar charts and
pie charts.

• Bar Charts
• A Bar chart consists of a
series of rectangles (or
Bars). The height of each
rectangle is determined by
the frequency of that
category.

• Line Chart can also be plotted in this data by connecting
the midpoints of each rectangle below:

Data Cleaning
• This includes checking the data for consistency treatment for
missing value. Preliminary consistency checks are made in
editing. Here we check the consistency in a extensive
manner.
• Consistency checks look for the data which are not
consistent outliers. Such data may be discarded or replaced
by the mean value.
• If missing values are the values which are unknown or not
answered by the respondent. In place of such missing values
some neutral value may be used.

Data adjusting
• Weight-assigning-
• The cases of educated people could be assigned higher
weights and of uneducated people could be assigned lower
weights in some survey.
• Variable Respecification-
• This involves creating new variables or modifying existing
variables. For example, if the usefulness of a certain product is
measured on 10 point scale, it may be reduced to 4 point
scale- ‘Very Useful’, ‘Useful’, ‘neutral’, ‘not useful’. Ratio of two
variables may also be taken to create a new variable.

• Dummy variables - is a variable which usually takes numerical values
based on the corresponding category in the original variable.
• 0 for non-smokers
• 1 for smokers
• Scale Transformation-
Scale transformation is done to ensure the comparability with other scales
or to make the data suitable for analysis. Different type of
characteristics are measured on different scales.
A common transformation is substracting all the values of a characteristic
by corresponding mean and dividing by corresponding standard
deviation.

Primary Data
• Primary data is one which is collected directly from
respondents using data collection methods like survey,
interviews, questionnaires, measurements, direct
observation or tabulation. Here, researchers are directly
involved in the collection of information required to
answer research questions.

Advantages of Primary Data
• Original in character.
• Meet the required needs of an investigator without editing.
• Quality of data is better as it has been collected by
persons, who were specifically trained for that purpose.
Thus, data is more accurate.
• Unbiased data.
• Targeted issues are addressed.
• Data interpretation is better.
• Greater Control.

Disadvantages of Primary Data
• High Costs
• Time Consuming
• Inaccurate feed backs
• More number of resources is required
• Direct and personal intervention has to be there

Secondary Data
• Secondary data is the data that already exists which has been collected by
some other person or organization for their use and is generally made
available to other researchers free or at concessional rate. Sources of
secondary data are journals, reports, government publications or professional
and research organizations.
• Collection of secondary data is less expensive in terms of money and time. e.g
If a researcher wants to analyse the weather conditions of different regions, he
can get the required information or data records from the meteorology
department. So, for the meteorology department, it is primary data, and for the
researcher the same data becomes secondary data.
• Secondary data may not always answer the special questions of a researcher.
Hence, a researcher should use judicious mix of primary and secondary data
to optimize the quality of research findings within allotted time and money.

Advantages of Secondary Data
• Secondary Data can Help to Identify, Clarify and Redefine the Research
Problem In situations, where the actual problems as research study cannot be
defined or is defined in an ambiguous way, the use of secondary data can
help clear the confusion.
• Secondary Data Might also hold a Solution to the Problem Sometimes; it
happens that precise data regarding the current research is already available
as secondary data. Hence, it might not be necessary to conduct a primary
data collection increase at all. This saves time and money
• Secondary Data may Provide Alternative Methods that can be used for
Primary Research Every research situation has custom made primary
research designed for it. When some published reports are gathered from
secondary sources, then gives an idea about the possible research
alternatives.

Disadvantages of Secondary Data
• May not be in target with the research problem.
• Quality and accuracy may pose a problem.

Methods of Data Collection
• Qualitative method
• Quantitative method

• Methods of collecting primary data, particularly in surveys and
descriptive researches. Important ones are:
(i)observation method (Checklist and Direct Observation)
(ii)interview method
(iii)through questionnaire
(iv) through schedules

• Observation is the systematic viewing/watching of specific
phenomenon or investigator’s own direct observation of
relevant people, actions and situations without asking
from the respondent for gathering primary data for a
particular study Example: Watching the life of street-
children provides a detailed description of their social life

Features of observation &Component of process of
observation
• Features of observation
• – Physical & mental activity-direct contact with the
environment.
• – Selective-Specific purpose of noting things relevant to
the study
• – Purposive & not informal
• – Grasps the significant events & occurrences
• – Should be exact & based on standardized tools of
research

Observation involves the active acquisition of information from a
primary source. Observation can also involve the perception and
recording of data via the use of scientific instruments. The best tools
for Observation are: Checklists and Direct Observation.
Checklists - state specific criteria, allow users to gather information
and make judgments about what they should know in relation to the
outcomes. They offer systematic ways of collecting data about
specific behaviors, knowledge, and skills.
Direct observation - This is an observational study method of
collecting evaluative information. The evaluator watches the subject
in his or her usual environment without altering that environment.

Interview
• The interview method of collecting data involves
presentation of oral-verbal stimuli and reply in terms of
oral-verbal responses. This method can be used through
personal interviews and, if possible, through telephone
interviews.
• Personal interview - structured and Unstructured
• Telephonic Interview

Types of interviews
• 1) Structured Interviews-involve the use of a set of pre-
determined questions and of highly standardized techniques of
recording, interviewer follows a rigid procedure laid down asking
questions in a form and order prescribed. ( used in descriptive
studies)
• 2) Unstructured interviews- flexibility of approach to
questioning-do not follows a system of pre-determined questions
and standardized techniques of recording information the
interviewer is allowed much greater freedom to ask, he may even
change the sequence of questions. ( used in exploratory studies

• 3) Focused group Interview- is a tool to understand people’s
thoughts, experience and feelings, about a product, service or
organization. Comments are recorded through note taking or
videotaped
• 4) Clinical/Depth Interview - it is concerned with broad underlying
feelings, opinion, emotions or motivations or with the course of
individual’s life experience about a product, service or organization
on the basis on interview guide.
• 5) Direct interviews/Interview Schedule –it is a set
questionnaire, when the researchers asks the questions and
records the respondent’s reply on the interview schedule.

• 6) Non-direct Interview- Interviewer encourage the respondent to
talk about the given topic with a base minimum of direct
questioning for the purpose eliciting the respondents feeling and
beliefs on the given topic.
• 7) Telephone- quick method of collecting information contacting
respondents on telephone. In this process interviewer can explain
questions not understood by the respondent.
• 8) Personal Interviewing- Personal interview can be used in any
type of questionnaire and can be conducted fairly quickly.
Interviewers can also show actual products, advertisements,
packages and observe and record their reactions and behaviour.

Merits of interview method
• a) More information can be obtained
• b) Greater flexibility
• c) Observation method can be applied
• d) Group discussions may also be
used
• e) Supplementary information can
collect
• • De-merits of interview method
• a) Very expensive
• b) More time consuming
• c) Basis of interviewer and
interviewee

Content Analysis
• Content Analysis is a systematic research method for
analyzing and making inferences from text and other
forms of qualitative information (Eg., from interviews,
focus groups, open-ended survey questions, documents,
videos )
• It uses a variety of analytic strategies to categorize,
compare, and contrast a corpus of data.
• Key trends and themes are identified through systematic
coding of the data.

video on content analysis
• https://m.youtube.com/watch?v=iZZABFd8cSA

Focus Group
• A focus group is a highly versatile and dynamic method of
colle information from a representative group of respondents.
The process generally involves a moderator who maneuvers
the discussion on the topic under study.
• There are a group of carefully-selected respondents who are
specifically invited and gathered at a neutral setting.
• The moderator initiates the discussion and then the group
carries it forward by holding a focused and an interactive
discussion. The technique is extensively used and at the
same time also criticized.

Projective Techniques (Indirect Interviewing)
• Projective techniqes are used for the collection of data
have been developed by psychologists to use projections
of respondents for inferring about underlying motives,
urges, or intentions which are such that the respondent
either resists to reveal them or is unable to figure out
himself. In projective techniques the respondent in
supplying information tends unconsciously to project his
own attitudes or feelings on the subject under study.
Projective techniques play an important role in
motivational researches or in attitude surveys.

• Association Techniques
• They essentially involve presenting a stimulus to the
respondents and he needs to respond with the first thing
that comes to his mind. This was found its earliest uses in
1936 by Houghton for advertising evaluations.
• The technique involves presenting a basket of words and
the respondent needs to respond instantly with the first
thing that comes to his mind.

sociometric analysis
• Sociometry involves measuring the choice, communication
and interpersonal relations of people in different groups.
The computations made on the basis of these choices
indicate the social attraction and avoidance in the group like
• ‘In the group(describe) with whom you would like to
work/interact socially with’
• ‘Out of the following (list of acquaintances) whom would
you find a acceptable neighbours on either side of your
home?’

Questionnaire
• Questionnaire is a document containing a list of
questions presented to a respondent for answers.
• • Mail- questionnaire sent by post to respondents
with covering letter or note introduce you; explain
the purpose of doing research and requesting to
send filled questionnaire within in reasonable time
to the researchers. The respondents read the
questions, interpret what is expected and then
write down the answers themselves.
• • Advantage
• – It can be used to collect large amounts of
information at a low cost
• – respondents may give more honest answers to
questions
• – Convenient for respondent’s who can answer
when they have time

Formalized and unconcealed questionnaire:
• This is the one that is indiscriminately and most frequently
used by all management researchers. For example, if a
new brokerage firm wants to understand the investment
behaviour of the population under study, they would
structure the questions and answers as follows

• This kind of structured questionnaire is easy to
administer, as one can see that the questions are self-
explanatory and, since the answer categories are defined
as well, the respondent needs to read and tick the right
answer. Another advantage with this form is that it can be
administered effectively to a large number of people at
the same time. Data tabulation and data analysis is also
easier to compute than in other methods.

Non-formalized, concealed:
• : If the objective of the research study is to uncover
socially unacceptable desires and latent or subconscious
and unconscious motivations, the investigator makes use
of questions of low structure and disguised purpose.
• The presumption behind this is that if the argument, the
situation or question is ambiguous, it is most likely that
the revelation it would result in would be more rich and
meaningful.

• A study conducted to measure to which segment should men’s
personal care toiletries (especially moisturizers and fairness
creams) be targeted, the investigator designed two typical
bachelors’ shopping lists. One with a number of monthly grocery
products as well as the normal male toiletries like shaving
blades, gels, shampoos, etc., and the other list had the same
grocery products and male toiletries but it had two additional
items—Fair and Handsome fairness cream and sensitive skin
moisturizer. The list was given to 20 young men to
conceptualize/describe the person whose list this is. The
answers obtained were as follows:

Content of the questionnaire
• the information needs and mode of administration has
been decided, is to determine the matter to be included as
questions in the measure. The decision to include or not
include certain questions depends upon a certain criteria.
Thus, the researcher needs to subject the questions
designed by him to an objective quality check in order to
ascertain what research objective/information need the
question would be covering before using any of the
framed questions.

• How essential is it to ask the question? In the course of
the research study, the researcher might formulate a
number of questions which he thinks address the
information needs of the study

• . For example, if one is studying the usage of plastic bags, then
demographic questions on age group, occupation, education and
gender might make sense but questions related to marital status,
family size and the state to which the respondent belongs are not
required as they have no direct relation with the usage or attitude
towards plastic bags.Sometimes, to gauge the information needs, the
researcher might have to ask multiple questions, even though they
might not seem to be related directly to the research objective. For
example, instead of asking shopkeepers, who own a shop in a
shopping centre, whether they would in the near future open an outlet
in a mall, a set of questions were asked to understand the retailers’
perception of shopping trends.

Criteria for Question Designing
• Step six of the questionnaire involves translating the
questions identified into meaningful questions. Utmost care
is needed to word the questioning, in a manner that the
question is clear and easy to understand by the
respondent. A confusing question or a poorly-worded
question might result in either no response or a wrong
response. Both of these are detrimental to the purpose of
the research study. There are certain designing criteria that
a researcher should adhere to when writing the research
questions. We will illustrate and discuss these individually.

Difference between Questionnaires and Schedules

Characteristics of a good questionnaire/ guidelines
• There are no hard and fast rules, only guidelines can be provided in
developing a questionnaire
• – Questions should be a simple and there should be no abbreviation
• – Maximum clarity should be maintained
• – Sequences of questions should be maintained
• – Questions should be an elegant appearance
• – It should attract the attention and generate interest of the informant.
• – The reliability and validity of the questions asked to be maintained
• – Question should contain polite, scope and coverage
• – Questions should be pre-testing

Pilot Study & pre-test
• A PILOT STUDY: is the process of carrying out a preliminary study, going
through the entire research procedure with a small sample before a large
scale filed study is termed as pilot survey
• • A PRE-TEST : usually refers to a small-scale trial of particular research
components. i.e. where a questionnaire is tested on a (statistically) small
sample of respondents, in order to identify any problems such as unclear
wording or the questionnaire taking too long to administer.
• • Uses of Pilot Study
• – To pre-test the suitability of questions
• – To generate fixed choice answers
• – To avoid unforeseen problems during the large survey
• – To provide experience and confidence to the interviewer

ARM Module 3 advanced research methodology

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