brm ppts.ppt

Business Research Methods
8/20/2022 1
Dr. Rajeev Sirohi LBSIM
Session 1

Research
• “systematic method consisting of defining the
problem, formulating a hypothesis, collecting the
data, analyzing the data and reaching certain
conclusions either in the form of solution towards
the concerned problem or in certain generalizations
for some theoretical formulation.”
• “systematic and objective process of gathering,
recording, and analyzing data for aid in making
business decisions (finance, marketing, human
resources etc.).”
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Applied and Basic Business
Research
• Applied business research
– conducted to address a specific business decision
for a specific firm or organization.
– Example:
• Should McDonald’s add Italian pasta dinners to its
menu?
• Which health insurance plan should a business provide
for its employees?

Applied and Basic Business
Research
• Basic business research (also called pure research)
– conducted without a specific decision in mind that usually
does not address the needs of a specific organization.
• Attempts to expand the limits of knowledge in general.
• Not aimed at solving a pragmatic problem.
– Example:
• Do consumers experience cognitive dissonance in low-involvement
situations?
• Does employee tenure with a company influence productivity?

Research Process
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Research process consists of series of actions or steps
necessary to effectively carry out research and the
desired sequencing of these steps.

Steps in the Research Process
1. Define research problem
2. Review the literature
3. Formulate hypotheses
4. Prepare research design
5. Collect data
6. Analyze data
7. Interpret and report
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Steps in the Research Process
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Defining the Research Problem
“ A problem well defined, is half solved.”
Research Problem refers to some difficulty which a
researcher experiences in the context of either
theoretical or practical situation and wants to obtain
a solution for the same

Components of a Research Problem
There must be
• Individual or group which has some difficulty
• Some objective(s) to be attained
• Some alternative means for attaining the objective
• Some doubt in the mind of the researcher with
regard to the selection of the alternatives
• Some environment to which the difficulty pertains

Techniques/Tasks Involved in Designing a
Problem
• Discussion with decision makers
• Interview with industry experts
• Secondary data analysis
• Qualitative research

Defining the Research Objectives
• Research objectives
– The goals to be achieved by conducting research.

Formulate Hypotheses
• Hypothesis
–Formal statement of an unproven
proposition that is empirically testable.
• Example: Giving employees one Friday off each
month will result in lower employee turnover.

Research Design
• A research design is the conceptual structure within
which research is conducted.
• A research design is a framework or blueprint for
conducting the research project. It details the
procedure necessary for obtaining the information
needed to structure and/or to solve research
problem.

Components of Research Design
• Design the exploratory, descriptive, and/or causal
phases of the research
• Sampling design
• Data collection design
• Measurement design
• Statistical design
• Software selection

When is Business Research
Needed?
• The determination of the need for research centers
on:
1. Time constraints
2. The availability of data
3. The nature of the decision to be made
4. Benefits versus costs (the value of the research
information in relation to costs)
• Will the payoff or rate of return be worth the investment?
• Will the information improve the quality of the managerial
decision enough to warrant the expenditure?
• Is the expenditure the best use of the available funds?

EXHIBIT 1.3 Determining When to Conduct Business Research

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Session 2

Types of Research (Design)

Types of Business Research
• Exploratory
• Descriptive
• Causal

Exploratory Research
• Exploratory Research
– Conducted to clarify ambiguous situations or
discover potential business opportunities.
– Initial research conducted to clarify and define the
nature of a problem.
• Does not provide conclusive evidence
• Subsequent research expected

Why Conduct Exploratory Research
(Purpose or Objective)
Exploratory research is used:
• Formulate or define a problem more precisely
• Identify alternative courses of action
• Develop working hypotheses from operational point of view.
• Isolate key variables and relationships for further
examination.
• Gain insights for developing an approach to the problem
• Establish priorities for further research

Techniques of Exploratory Research
• Secondary Data Analysis (The survey of concerning
literature)
• Expert Surveys
• Case Studies
• Pilot Studies for Qualitative Analysis
-Direct or Non disguised techniques
-Indirect or Disguised Techniques

Descriptive Research Design
• Describes characteristics of objects, people, groups,
organizations, or environments.
– Considerable understanding of the nature of the
problem exists.
– Does not provide direct evidence of causality.
The objective of such a study is to answer the (Six
Ws) “Who, What, When, Where, Why, and Way
(How)” of the subject under investigation.

Why Conduct Descriptive Research
(Purpose or Objective)
• To describe the characteristics of relevant groups,
such as consumers, salespeople, organizations,
market areas.
• To estimate the percentage of units in a specified
population exhibiting a certain behaviour.
• To determine the perception of product
characteristics.
• To determine the degree to which marketing
variables are associated.
• To make specific predictions.

• Cross-sectional design involves the collection of
information from any given sample of population
elements only once.
-Single cross-sectional design: Only one sample of
respondent is drawn from the target population, and
information is obtained from this sample only once.

-Multiple cross-sectional design: There are two or more
sample of respondents, and information from each
sample is obtained only once.
e.g. How did Indian people rate the performance of
Narendra Modi immediately after the demonetization?

• Longitudinal design: A fixed sample (or samples) of
population elements is measured repeatedly on the
same variables.
e.g. How did Indian people change their view of Modi’s
performance during the demonetization?

Causal research Design
A causal research investigates the cause and effect
(causal) relationship between two or more variables.
The Researcher try to understand the phenomena in
terms of conditional statements of the form “If x,
then y.”

Causal research is appropriate for the following
purposes:
• To understand which variables are the causes
(independent variables) and which variables are the
effect (dependent variables) of a phenomenon.
• To determine the nature of relationship between the
causal variables and the effect to be predicted.

Causal research requires a planned and structures
design. In causal research, independent variables
(causes) are manipulated in relatively controlled
environment. The effect of this manipulation on one
or more dependent variables is then measured to
infer causality. The main method of causal research is
experimentation.

Comparison of Basic Research Design
Exploratory Descriptive Causal
Objective Discover ideas and
insights
Describe market
characteristics or
functions
Determine cause
and effect
relationships
Characteristics Flexible, Versatile,
often the front end
of total research
design
Rigid, Marked by the
prior formulation of
specific hypothesis,
preplanned and
structured design
Manipulation of
one or more
independent
variables, control of
other mediating
variables
Methods Expert surveys,
Secondary data
analysis,
Pilot studies for
qualitative
analysis, Case
studies
Secondary data
Surveys/Interview
Observational and
other data
Experiments

Comparison of Basic Research Design
Exploratory Descriptive Causal
Example “Our sales are
declining for no
apparent reason?”
“What kinds of
new products are
fast-food
customers
interested in?”
“What kind of
people patronize our
stores compared to
our primary
competitor?”
“What product
features are most
important to our
customers?”
“Will consumer buy
more products in
blue package?”
“Which of two
advertising
campaign will be
more effective?”

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Session 3

Problem Definition: The foundation of
business research
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Good Decisions Start with a Good
Problem Definition
• Decision Statement
– A written expression of the key question(s) that
the research user wishes to answer.
• Problem Definition
– The process of defining and developing a decision
statement and the steps involved in translating it
into more precise research terminology, including
a set of research objectives.

The Problem-Definition Process
• Problems Mean Gaps
A problem occurs when there is a difference
between the current conditions and a more
preferable set of conditions.
– Business performance is worse than expected
business performance.

EXHIBIT 6.2 The Problem-Definition Process

Understand the situation (Business
Decision)
• Situation Analysis
– The gathering of background information to
familiarize researchers and managers with the
decision-making environment.
– Starts with an interview between the researcher
and management

Understand the Business Decision
• Identifying Symptoms
– Interrogative techniques
• Asking multiple what, where, who, when, why,
and how questions about what has changed.
– Probing
• An interview technique that tries to draw
deeper and more elaborate explanations from
the discussion.

Writing Managerial Decision Statements
and Corresponding Research Objectives
• Decision statements must be translated into
research objectives.
– Once the decision statement is written, the
research essentially answers the question, “What
information is needed to address this situation?”
• Research objectives are the deliverables of
the research project.

Determine the Unit of Analysis
• Unit of Analysis
– Indicates what or who should provide the data and at what
level of aggregation.
• Individuals (such as customers, employees, and owners)
• Households (families, extended families, and so forth)
• Organizations (businesses and business units)
• Departments (sales, finance, and so forth)
• Geographical areas
• Objects (products, advertisements, and so forth).

Writing Research Questions and
Research Hypotheses
• Research Questions
– Express the research objectives in terms of
questions that can be addressed by research.
– Help to develop well-formulated, specific
hypotheses that can be empirically tested.
– Help the researcher design a study that will
produce useful results.

How Much Time Should Be Spent
on Problem Definition?
• Budget constraints usually influence how
much effort is spent on problem definition.
• The more important the decision faced by
management, the more resources should be
allocated toward problem definition.
• The time taken to identify the correct
problem is usually time well spent.

Management Decision Problem Vs
Research Problem
Management Decision Problem Research Problem
1. Asks what the decision maker
needs to do.
1. Asks what information is needed
and how it should be obtained.
2. Action oriented 2. Information oriented
3. Focuses on symptoms 3. Focuses on underlying causes
4. Examples
•Should a new product be
introduced?
•Should the advertising campaign be
changed?
•Should the price of brand be
increased?
4. Examples
• To determine consumer preferences
and purchase intentions for the
proposed new product.
•To determine the effectiveness of
the current advertising campaign
•To determine the price elasticity of
demand and the impact on sales and
profits of various level of prices

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Session 4

Qualitative Research Tools
©

Qualitative Research
• Provides insights and understanding of the
problem setting.
• Is used for generating hypotheses and
identification of variables

What is Qualitative Research?
• Qualitative business research
– Research that addresses business objectives through
techniques that allow the researcher to provide
elaborate interpretations of phenomena without
depending on numerical measurement
• Its focus is on discovering true inner meanings and new
insights.
• Researcher-dependent
– Researcher must extract meaning from unstructured
responses such as text from a recorded interview etc.

Uses of Qualitative Research
• Qualitative research is useful when:
– People are unwilling to give truthful answers to questions
– People may be unable to provide accurate answers to
questions
– It is difficult to develop specific and actionable problem
statements or research objectives.
– The research objective is to develop a detailed and in-
depth understanding of some phenomena.
– The research objective is to learn how a phenomenon
occurs in its natural setting.

Qualitative “versus” Quantitative
Research
• Quantitative business research
– Descriptive and conclusive
• Addresses research objectives through empirical
assessments that involve numerical measurement and
statistical analysis.
• Qualitative business research
– Exploratory
• Uses small versus large samples
• Asks a broad range of questions versus structured
questions
• Subjective interpretation versus statistical analysis

Contrasting Exploratory and
Confirmatory Research
• Qualitative data
– Data that are not characterized by numbers but
rather are textual, visual, or oral.
• Focus is on stories, visual portrayals, meaningful
characterizations, interpretations, and other
expressive descriptions.
• Quantitative data
– Represent phenomena by assigning numbers in
an ordered and meaningful way.

Qualitative “versus” Quantitative Research
Qualitative Research Quantitative Research
Objective To gain a qualitative
understanding of the
underlying reasons
and motivations
To quantify the data
and generate results
from the sample to the
population of interest
Research design
Sample
Exploratory
Small
Descriptive and causal
Large
Data collection Unstructured Structured
Data analysis Non statistical Statistical
outcome Develop an initial
understanding
Recommend a final
course of action

Qualitative Research Techniques
• Non disguised (direct) approach
-Focus group interview
-Depth interview
• Disguised (indirect) approach
-Projective techniques
Association technique
Completion technique
Construction technique
Expressive technique

Focus Group Interview
• An unstructured, free-flowing interview with a small
group (6-10 people) led by a moderator who
encourages dialogue among respondents.
• Advantages:
1. Relatively fast
2. Easy to execute
3. Allow respondents to piggyback off each other’s ideas
4. Provide multiple perspectives
5. Flexibility to allow more detailed descriptions
6. High degree of scrutiny

Focus Group Respondents
• Group Composition
– 6 to 10 people
– Relatively homogeneous
– Similar lifestyles and
experiences

The Focus Group Moderator
• Moderator
– A person who leads a focus group interview and
insures that everyone gets a chance to speak and
contribute to the discussion.
• Qualities of a good moderator:
– Develops rapport with the group
– Good listener
– Tries not to interject his or her own opinions
– Controls discussion without being overbearing

Planning a Focus Group Outline
• Discussion guide
– Includes written introductory comments informing
the group about the focus group purpose and
rules and then outlines topics or questions to be
addressed in the group session.

Disadvantages of Focus Groups
• Focus groups:
– Require objective, sensitive, and effective
moderators.
– May not be useful for discussing sensitive topics in
face-to-face situations.
– Cost a considerable amount of money (renting
facilities and equipment, recruiting of
respondents, paying respondents, researcher
costs etc.)

Depth Interviews
• Depth interview
– A one-on-one interview between a professional
researcher and a research respondent conducted
about some relevant business or social topic.
– Laddering: a particular approach to probing,
asking respondents to compare differences
between brands at different levels.

Projective Techniques
• Association techniques
An individual is presented with a stimulus and
asked to respond with the first things that
comes to mind.
-Word association
• Completion techniques
Respondent is asked to complete an incomplete
stimulus situation.
Sentence completion and story completion.

Projective Techniques
• Construction techniques
Respondent is asked to construct a response in the
form of story or description from the picture or
cartoons
• Expressive techniques
Respondents are presented with a verbal or visual
situation and asked to relate the feelings and
attitudes of the other people to the situation.
Role playing

Secondary Data Research

• Secondary Data
Secondary data are those which have already been
collected by someone else prior to and for a
purpose other than the current problem at hand.

• Advantages
Easily accessible or available
Relatively inexpensive (economical) than acquiring
primary data
Quickly obtained (save time in data collection)
Requires no access to subjects
Wide coverage (space and time)

•Disadvantages
Data may not suitable or relevant to the current
problem
Data may be lacking in accuracy
Inappropriate units of measurement
Too old

EXHIBIT 8.2 Common Research Objectives for Secondary-Data Studies

Classification of Secondary Data
(Sources of Secondary Data)
• Internal data
-Ready to use
-Require further processing
Example Sales invoice, Customer complaints and service record,
Accounting information
• External data
-Published materials
-Computerized data bases

Published Material
• Government Sources
Census data: demographic information about population of country
CSO: National Accounts Statistics once a year – national income
The Director General of Commercial Intelligence: Monthly statistics
about foreign trade of India
Annual publication of planning commission: Statistics relating to the
Indian economy
RBI Bulletin: Merger and acquisition
• Non Government Sources
Business publication: books, periodicals, journals, newspaper,
magazines, reports, and trade literature
Directories

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Session 5
Survey Research

Survey Research
• Purpose: to collect primary data – data
gathered and assembled specifically for the
project at hand.

Survey Research
• Survey Objectives
– Surveys attempt to describe what is happening,
what people believe, what they are like, or to
learn the reasons for a particular business activity.
– Survey research is descriptive research:
• Identifying characteristics of target markets
• Measuring consumer attitudes
– Surveys can be both quantitative and qualitative.

Interviews as Interactive Communication
• Interactive Survey Approaches
– Those that allow spontaneous two-way
interaction between the interviewer and the
respondent.
– Can be either personal or electronic.
• Noninteractive Media
– Those that do not facilitate two-way
communication and are largely a vehicle by which
respondents give answers to static questions.
• Self-administered mail and Internet surveys

Personal Interviews
• A personal interview is a form of direct
communication in which an interviewer asks
respondents questions face-to-face.
– Versatile and flexible
– Truly interactive

Advantages of Personal Interviews
Personal
Interviews
Opportunity
for Feedback
Probing Complex
Answers
Length of
Interview
Completeness of
Questionnaire
High
Participation
Props and
Visual Aids

Disadvantages of Personal
Interviews
Cost
Interviewer
Influence
Lack of
Anonymity of
Respondent
Personal
Interviews

Door-to-Door Interviews
• Personal interviews conducted at
respondents’ doorsteps in an effort to
increase the participation rate in the survey.
• Callbacks
– Attempts to recontact individuals selected for a
sample who were not available initially.

Mall Intercept Personal Interview
• Personal interviews conducted in a shopping
mall.
• Interviewers typically intercept shoppers at a
central point within the shopping center or at
the main entrance.

Telephone Interviews
• Telephone Interviews
– Personal interviews conducted by telephone.
– The mainstay of commercial survey research.
– “No-call” legislation has limited this capacity.

Types of Telephone Interviews
• Traditional Telephone Interviewing
– Involve phoning a sample of respondents and asking them
a series of questions. The interviewers uses a paper
questionnaire and record the responses with a pen/pencil.
• Computer-Assisted Telephone Interviewing (CATI)
– Uses a computerized questionnaire administered to
respondents over the telephone.
– The computer replaces a paper questionnaire and pencil
and the miniheadset substitutes for a telephone.

Self-Administered Questionnaires
• Surveys in which the respondent takes the
responsibility for reading and answering the
questions.

EXHIBIT 10.1 Self-Administered Questionnaires Can Be Either Printed or Electronic

Mail Questionnaires
• Characteristics of Mail Questionnaires
– Geographical flexibility
– Cost
– Respondent convenience
– Anonymity of respondent
– Absence of interviewer
– Standardized questions
– Length of mail questionnaire

Self-Administered Questionnaires
• Response Rate
– The number of questionnaires returned or
completed divided by the number of eligible
people who were asked to participate in the
survey.

Fax Surveys
• A survey that uses fax machines as a way for
respondents to receive and return
questionnaires.
• Advantages
– Reduce sender’s printing and postage costs
– Is quicker than traditional mail surveys
• Disadvantage
– Only respondents with fax machines who are willing
to exert the extra effort will return questionnaires.

E-Mail Surveys
• Surveys distributed through electronic mail.
• Ways to contact respondents:
– Include a questionnaire in the body of an e-mail.
– Distribute questionnaire as an attachment.
– Include a hyperlink within the body of an e-mail.
• Advantages
– Speed of distribution
– Lower distribution and processing costs
– Faster turnaround time
– More flexibility
– Less handling of paper questionnaires
• Disadvantage
– Not all e-mail systems have the same capacity

Internet Surveys
• A self-administered questionnaire posted on
a Web site.
– Respondents provide answers to questions
displayed online by highlighting a phrase, clicking
an icon, or keying in an answer.

Selecting the Appropriate Survey
Approach
• Questions to be answered:
– Is the assistance of an interviewer necessary?
– Are respondents interested in the issues being
investigated?
– Will cooperation be easily attained?
– How quickly is the information needed?
– Will the study require a long and complex
questionnaire?
– How large is the budget?

Selecting the Appropriate Survey
Approach
Parameters Telephone
Interview
Method
Personal
Interview
Method
Mail-
Questionna
ire Method
Funds Restricted Available Limited
Time Restricted Available Sufficient
Precision Average High Low
Information Less
information
is desired
More
information
is desired
More
information
is desired

Errors in Survey Research
• Random Sampling Error
– A statistical fluctuation that occurs because of chance
variation in the elements selected for a sample.
• Systematic Error (non sampling errors)
– Error resulting from some imperfect aspect of the
research design that causes respondent error or from
a mistake in the execution of the research.
– Sample Bias: A persistent tendency for the results of
a sample to deviate in one direction from the true
value of the population parameter.
– Two types: Respondent error and Administrative error

EXHIBIT 9.1 Categories of Survey Errors

Respondent Error
• Respondent Error
– A category of sample bias resulting from some
respondent action or inaction such as
nonresponse or response bias.
• Nonresponse Error
– The statistical differences between a survey that
includes only those who responded and a perfect
survey that would also include those who failed to
respond.

Respondent Error
• Nonrespondents
–People who are not contacted or who
refuse to cooperate in the research.
• No contacts: people who are not at home or
who are otherwise inaccessible on the first and
second contact.
• Refusals: People who are unwilling to
participate in a research project.

Response Bias
• Deliberate Falsification
– Occasionally people deliberately give false
answers.
• Misrepresent answers to appear intelligent
• Conceal personal information
• Avoid embarrassment
– Average-person hypothesis:
• Individuals may prefer to be viewed as average, so they
alter their responses to conform more closely to their
perception of the average person.

Response Bias
• Unconscious Misrepresentation
– Response bias can arise from the question format,
the question content, or some other stimulus
that affects their response to a question.
– Sources of misrepresentation:
• Misunderstanding the question
• Unable to recall details
• Unprepared response to an unexpected question
• Inability to translate feelings into words
• After-event underreporting

Types of Response Bias
• Acquiescence Bias
– A tendency to agree with all or most questions.
• Extremity Bias
– The tendency of some Individuals to use extremes when
responding to questions.
• Interviewer Bias
– The presence of the interviewer influences respondents’
answers.
• Social Desirability Bias
– Bias in responses caused by respondents’ desire, either
conscious or unconscious, to gain prestige or appear in a
different social role.

Administrative Error
• An error caused by the improper administration
or execution of the research task.
– Data-processing error: incorrect data entry, incorrect
computer programming, or other procedural errors
during data analysis.
– Sample selection error: improper sample design or
sampling procedure execution.
– Interviewer error: mistakes made by interviewers
failing to record survey responses correctly.
– Interviewer cheating: filling in fake answers or
falsifying questionnaires by an interviewer.

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Session 6-7

Observation Methods

Observation in Business Research
• Observation
– a systematic process of recording behavioral
patterns of people, objects, and events as they
happen.
• The observer does not question or communicate
with the people.
• It is the most commonly method in studies relating
to behavioural science.

Observation Method
Advantages:
• The information obtained relates what is currently
happening.
• The method is independent of respondent’s
willingness to respond.
• Data are free from distortions, inaccuracies, or other
response biases.
• This method is suitable in studies which deals with
the respondents who are not capable of giving verbal
reports of their feelings.

Observation Method
Disadvantages:
• It is an expensive method.
• The information provided by this method is very
limited.
• Training is required for data collection.
• Less validity.

Types of observation method
Personal observation
A researcher observes actual behavior as it occurs. The
observer merely records what takes place.
Example: A researcher might record traffic counts and
observe traffic flow in a department store.

Mechanical observation
Mechanical devices rather than human observers
record the phenomenon being observed. They are
used for continuously recording on-going behavior
for later analysis.
Example: On-site cameras
• Television Monitoring
– Computerized mechanical observation used to
obtain television ratings.

Structured observation
• The observation is characterized by a careful definition
of the units to be observed, the style of recording the
observed information, standardized conditions of
observation, and the selection of pertinent data of
observation.
• Structured observation is considered appropriate in
descriptive studies.

Unstructured observation
• The observation is to take place without the
characteristics (as in structured observation) to be
thought of in advance.
• Unstructured observation is considered appropriate in
exploratory studies.

Controlled observation
Observation takes place according to pre-arranged plans,
involving experimental procedures.
Controlled observation takes place in various experiments
that are carried out in laboratory or under controlled
conditions.
Such observation has a tendency to supply formalized data
upon which generalizations can be built with some
degree of assurance.

Uncontrolled observation
• Observation takes place in the natural setting.
• The major aim of uncontrolled observation is to get a
spontaneous picture of life and persons.
• Uncontrolled observation is used in case of exploratory
researches.

Ethical Issues in the Observation of Humans
• Issues
– Respondent’s right to privacy
• Researchers feel comfortable collecting
observational data if:
– The observed behavior is commonly performed in
public where others can observe the behavior.
– The behavior is performed in a setting that assures
the anonymity of the person being observed.
– The observed person has agreed to be observed.

Experimental Research

Experiment Method
• The only research method that can identify cause-
and effect relationship.
• Subjects
– Participants in experimental research are referred to as
subjects rather than respondents.
• Independent Variables
• Dependent variable
• Examples
– Do people with pink shirts get more success in job
interviews?

Experiment Method
– What effect does caffeine have on memory?
– Scores of test improve with time spent studying.
– Does aggression increase with consumption of alcohol?
• Extraneous variables

Designing an Experiment to Minimize
Experimental Error
1. Manipulation of the Independent Variable
– Experimental treatment: the way an experimental
variable is manipulated.
• Categorical variables: described by class or quality
• Continuous variables: described by quantity (level)
– Experimental Group
• A group of subjects to whom an experimental treatment is
administered.
– Control Group
• A group of subjects to whom no experimental treatment is
administered.

Designing an Experiment (cont’d)
• Repeated Measures
– Experiments in which an individual subject is
exposed to more than one level of an
experimental treatment.

2. Selection and Measurement of the
Dependent Variable
– Selecting dependent variables that are relevant
and truly represent an outcome of interest is
crucial.
– Choosing the right dependent variable is part of
the problem definition process.
• Thorough problem definition will help the researcher
select the most important dependent variable(s).

3. Selection and Assignment of Test Units
– Test units: the subjects or entities whose responses to
treatment are measured or observed.
• Sample Selection And Random Sampling Errors
– Systematic or nonsampling error
occur if the sampling unit in an experimental cell are
somehow different than the units in another cell, and this
difference affects the dependent variable.
• Subject selection, experimental design, and unrecognized
extraneous variables

– Overcoming sampling errors
• Randomization: random assignment of subject and
treatments to groups.
• Matching
4. Control over extraneous variables

Practical Experimental Design
Issues
• Basic versus Factorial Experimental Designs
– Basic experimental designs – a single independent variable and a
single dependent variable.
– Factorial experimental design – allows for an investigation of the
interaction to two or more independent variables.
• Laboratory Experiment
– A situation in which the researcher has more complete control over
the research setting and extraneous variables.
• Field Experiments
– Research projects involving experimental manipulations that are
implemented in a natural environment.

EXHIBIT 12.5 The Artificiality of Laboratory versus Field Experiments

Laboratory
Experiment
Field
Experiment
Artificial: Low Realism
Few Extraneous
Variables
High control
Low Cost
Short Duration
Subjects Aware of
Participation
Natural: High Realism
Many Extraneous
Variables
Low control
High Cost
Long Duration
Subjects Unaware of
Participation
Laboratory versus Field
Experiments

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Session 8

8/20/2022 121
Measurement and Scaling

Measurement and Scaling
Measurement
• The assignment of numbers or symbols to
characteristics of objects according to certain
prespecified rules.
Scaling
• The generation of a continuum upon which
measured objects are located.

Primary Scales of Measurement
Nominal Scale:
– Assigns a value to an object for identification or
classification purposes.
– Most elementary level of measurement.
e.g. numbers assigned to football
players

Ordinal Scale:
– Ranking scale in which numbers are assigned to
objects to indicate the relative extent to which the
objects posses some characteristics.
– Indicates relative position, not the magnitude of
the differences between the objects.
– Have nominal properties.
– e.g. Ranking of teams in a tournament

Interval Scale:
– Numerically equal distances on the scale represents
equal values in the characteristics being measured.
– Contains all the information of nominal and ordinal
scale, but it also allow to compare the differences
between objects.
– There is constant or equal interval between scale values.
e.g. Temperature Scale, Calendar Time

Ratio Scale:
– Highest form of measurement.
– Have all the properties of the nominal, ordinal,
and interval scales with the additional attribute of
representing absolute quantities.
– Absolute zero.
e.g. Height, Weight, Age, Sales Revenue, Stock Price

Classification of Scaling Techniques
• Comparative Scales involve the direct comparison of
stimulus objects with one other. E.g. respondents
may be asked whether they prefer Coke or Pepsi.
Comparative scale must be interpreted in relative terms
and have only ordinal properties and hence it is
referred as non-metric scaling.

• Paired Comparison Scaling (Attitude Measurement Scale)
In paired comparison scaling, a respondent is presented with
two objects at a time, and asked to select one object in the
pair according to some criterion.
Suppose the respondent is asked to show his preference from
amongst five brands of tea A,B,C,D and E with respect to the
flavour.
Number of pairs= [(n)(n-1)/2]
Where n is number of brands

• Rank Order Scaling
In rank order scaling, respondents are presented with
several objects simultaneously and asked to order or
rank them according to some criterion.
e.g. respondents may be asked to rank brands of
toothpaste according to overall preference

• Rank Order Scaling
Brand Rank
Colgate ___
Closeup ___
Pepsodent ___
Babul ___
Rank 1 means most preferred brand
Rank 4 means least preferred brand

• Constant Sum Scaling
A comparative scaling technique in which respondents
are required to allocate a constant sum of units such
as points among a set of stimulus objects with
respect to some criterion.

Example:
• Divide 100 points among each of the following
attributes of two-wheeler according to your
preference:
• Price ______
• Mileage _____
• Quality _________
• Power _______

• Non Comparative Scaling Techniques
The scaling technique in which each stimulus object is
scaled independently of the other objects in the
stimulus set. The resulting data are generally
assumed to be interval or ratio data. Non
comparative scales also referred as metric scales.

• Continuous Rating Scale or Graphic Rating Scale or
Thurstone Interval Scale (Attitude Measurement Scale)
Respondents rate the objects by placing a mark at the
appropriate position on a line that runs from one
extreme of the criterion variable to the other.

• Continuous Rating Scale or Graphic Rating Scale or
Thurstone Scale (Attitude Measurement Scale)
e.g.
Q How would you rate Vishal Mega Mart as a
department store?
Probably the worst ______________ Probably the best

• Likert Scale (Attitude Measurement Scale)
The respondents are asked to indicate a degree of
agreement or disagreement with each of a series of
statements about the stimulus objects.
Typical five response categories: “strongly disagree,”
“disagree,” “neither agree nor disagree,” “agree,” and
“strongly agree.”

• Likert Scale (Attitude Measurement Scale)
Example:
It is more fun to play a tough, competitive tennis
match than to play an easy one.
___Strongly Disagree ___Disagree ___Neither
Agree nor Disagree ___Agree ___Strongly Agree

• Semantic Differential Scale (Attitude Measurement
Scale)
The semantic differential is a seven-point rating scale
with endpoints associated with bipolar levels that
have semantic meaning.
Individual items on a semantic differential scale may be
scored on either a -3 to +3 or 1 to 7 scale.

• Semantic Differential Scale (Attitude Measurement
Scale)
Example
Fun & Food is
Exciting ___ : ___ : ___ : ___ : ___ : ___ : ___ Calm
Interesting ___ : ___ : ___ : ___ : ___ : ___ : ___ Dull

• Stapel Scale
It is a unipolar rating scale with 10 categories
numbered from -5 to +5, without a neutral point
(zero). This scale is usually presented vertically.
Respondents are asked to indicate how accurately or
inaccurately each term describes the object by
selecting an appropriate numerical response
category.

• Stapel Scale
e.g. Please evaluate how accurately each word or
phrase describes VMM. You can select any number,
from +5 for phrases you think are very accurate, to -5
for phrases you think are very inaccurate.

+5 +5
+4 +4
+3 +3
+2 +2 x
+1 +1
High Quality Poor Service
-1 -1
-2 -2
-3 -3
-4 x -4
-5 -5

Three Criteria for Good
Measurement
Sensitivity
Reliability Validity
Good
Measurement

Reliability
• Reliability
– The degree to which measures are free from
random error and therefore yield consistent
results.
– An indicator of a measure’s internal consistency.
• Split-half Method
– Assessing internal consistency by checking the
results of one-half of a set of scaled items against
the results from the other half.

Reliability
• Coefficient alpha (α)
– The most commonly applied estimate of a
multiple item scale’s reliability.
• Test-retest Method
– Administering the same scale or measure to the
same respondents at two separate points in time
to test for stability.
– Represents a measure’s repeatability.

Validity
• Validity
– The accuracy of a measure or the extent to which a
score truthfully represents a concept.
• Does a scale measure what was intended to be
measured?
• Establishing Validity:
– Is there a consensus that the scale measures what it
is supposed to measure?
– Does the measure correlate with other measures of
the same concept?
– Does the behavior expected from the measure
predict actual observed behavior?

Reliability and Validity on Target

Sensitivity
• Sensitivity
– A measurement instrument’s ability to accurately
measure variability in stimuli or responses.
– Generally increased by adding more response
points or adding scale items.

8/20/2022 149
Session 9

Questionnaire Design
A questionnaire is a formalized set of questions for
obtaining information from the respondents.

Objectives of Questionnaire
• It must translate the information needed into a set of
specific questions.
• A questionnaire must uplift, motivate, and encourage
the respondents to become involved in the interview,
to cooperate, and to complete the interview.
• A questionnaire must minimize response error.

Questionnaire Design Process
1. Specify the information needed
2. Specify the type of interviewing method
3. Determine the content of individual questions
• Is the question necessary?
• Are several questions needed instead of one?

e.g. “Do you think Coca-Cola is a tasty and refreshing
soft drink?”
Double-barreled question: A single question that
attempts to cover two issues. Such questions can be
confusing to respondents and results in ambiguous
responses.

To obtain the required information, two distinct
questions should be asked:
“Do you think Coca-Cola is a tasty soft drink?”
“Do you think Coca-Cola is a refreshing soft drink?”

4. Design the questions to overcome the respondent’s
inability and unwillingness to answer
(a) Overcoming inability to answer
• Is the respondent informed?
Filter question: An initial question in a questionnaire
that screens potential respondents to ensure they
meet the requirement of the sample

• Can the respondent remember?
e.g. How many gallons of soft drinks did you consume
during the last four weeks?
How often do you consume soft drinks in a week?
(i) Once in a week (ii) 2 to 3 times
(iii) 4 to 5 times (iv) 6 or more

• Can the respondent articulate (responses)?
(b) Overcoming unwillingness to answer
• Effort required of the respondents
e.g. 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 follow, please check all the departments
from which you purchased merchandise on your
recent shopping trip to a department store. (Correct)
(i) Women’s dress
(ii) Men’s apparel
(iii) Children’s apparel
(iv) Cosmetics
(v) Other (please specify)

• Legitimate purpose
• Sensitive information
5. Choosing question structure
(i) Unstructured questions: Unstructured questions
are open-ended questions that respondents
answer in their own words, also referred as free-
response or free-answer questions.
e.g. Who is your favourite political figure?

(ii) Structured questions: Structured questions specify
the set of response alternatives and the response
format. A structured question may be multiple
choice questions , dichotomous questions.
Multiple choice questions: The researcher provides a
choice of answers and respondents are asked to
select one or more of the alternatives given.

e.g. How did you make your reservation?
(i) Airline website
(ii) Airline ticket office
(iii) Travel agent
(iv) Other (Please specify)

Dichotomous questions: A dichotomous question has
only two response alternatives. Yes or no, agree or
disagree , and so on. Often, the two alternatives are
supplemented by a neutral alternative, such as “no
opinion”, “don’t know”, “both”, or “none”.
e.g. Do you intend to buy a new car within the next six
months?
(i) Yes (ii) No (iii) Don’t know

6. Choosing question wording
• Define the issue
e.g. Which brand of shampoo do you use?
Which brands of shampoo have you personally used in
home during the last month?

• Use ordinary words
e.g. Do you think distribution of soft drinks is
adequate?
Do you think soft drinks are readily available when you
want to buy them?

• Use unambiguous words
e.g. In a typical month, how often do you shop in
department stores?
(i) Never
(ii) Occasionally
(iii) Sometimes
(iv) Often
(v) Regularly

e.g. In a typical month, how often do you shop in
department stores?
(i) Less than once
(ii) 1 or 2 times
(iii) 3 or 4 times
(iv) More than 4 times

• Avoid leading or biasing questions
e.g. Do you think that patriotic Indians should buy
imported products when that would Indian labour
out of work?
(i) Yes
(ii) No
(iii) Don’t know

e.g. Do you think that Indians should buy imported
products?
(i) Yes
(ii) No
(iii) Don’t know

7. Determining the order of questions
• Basic information
• Classification information
• Identification information
8. Form and Layout
9. Reproduction of the Questionnaire

10. Pretesting
Pretesting refers to the testing of the questionnaire on
a small sample of respondents to identify and
eliminate potential problems.

Difference between Questionnaire and Schedule
Questionnaire Schedule
1. The questionnaire is generally
sent through mail to respondents
to be answered as specified in a
covering letter, but without further
assistance from the sender.
1.The schedule is generally filled
out by the enumerator or the
research worker, who can interpret
questions when necessary.
2. Collection of data through
questionnaire is relatively cheap
and economical.
2. Collection of data through
schedules is relatively more
expensive.
3. It is not always clear as to who
replies.
3. The identity of the respondent is
known.

Difference between Questionnaire and Schedule
Questionnaire Schedule
4. Personal contact is not possible. 4. Direct personal contact is
established with respondents.
5. Information can be collected only
when respondents are literate and
cooperative
5. Information can be gathered
even when the respondents
happens to be illiterate.
6. The success of questionnaire
method lies more on the quality of
the questionnaire itself.
6. The success of schedule method
depends upon the honesty and
competency of enumerators.
7. Along with questionnaire,
observation can not be used.
7. Along with schedule, observation
can also be used.
8. Non-response is usually high as
many people do not respond.
8. Non-response is generally low, as
schedules are filled by
enumerators.

8/20/2022 173
Session 10

8/20/2022 174
Sampling Design and Procedure

Sampling Terminology
Population (Universe): A population is the aggregate of all
the elements that share some common set of
characteristics and that comprise the universe for the
purpose of research problem. Example proportion of
consumers who are loyal to a particular brand of
toothpaste.
Population Element: An individual member of the
population.

Sampling Terminology
Census: A census involves a complete enumeration of
the elements of a population.
Sample: A subset, or some part, of a larger population
selected for participation in the study.
Sample characteristics, called statistics, are then used
to make inferences about population parameters.

The Sampling Design Process
• Define the target population
• Determine the sampling frame
• Select a sampling technique
• Determine the sample size
• Execute the sampling process

Define the target population
The target population is the collection of elements or
objects that possess the information sought by the
researcher and about which inferences are to be
made.

The target population should be defined in terms of
elements, sampling units, extent, and time.
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.

Extent refers to geographical boundaries, and the time
factor is the time period under consideration.
Example: The target population for the department
store project can be defined as follows:
Elements – male and female head of the household
Sampling units – households
Extent – NCR
Time - 2019

Determine the Sampling Frame
A sampling frame is the representation of the elements
of the target population. It consists of a list or set of
directions for identifying the target population.
Example:
 Listing of all students attending university
 Employee roll
 Listing of stocks at Stock Exchange

Select a Sampling Technique
It is the way the elements/sampling units are to be
selected.
Sampling techniques are of two types:
• Non Probability sampling techniques
• Probability sampling techniques

Non Probability sampling techniques
• Convenience sampling
• Judgemental sampling
• Quota sampling
• Snowball sampling

Convenience sampling
Convenience sampling attempts to obtain a sample of
convenient elements. The respondents are selected because
it is easy to access them.
Example: Students in the class, people on Street, friends,
department store etc.

Judgemental sampling
Population elements are selected on the basis of
judgement of researcher.
The researcher exercising judgement or expertise,
chooses the elements to be included in the sample
because he believes that they are the representative of
the population of interest.

Quota sampling
Two-stage sampling
First stage: 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 in the target population.
Second stage: Sample elements are selected based on
convenience and judgement.

Snowball sampling
Initial group of respondents is selected at random and
subsequent respondents are selected based on
referrals.
Objective: To determine the characteristics that are
rare in the population
Example: Users of particular government or social
services

Probability sampling techniques
• Simple random sampling
• Systematic sampling
• Stratified sampling
• Cluster sampling

Simple Random Sampling
In SRS, each element in the population has a known
and equal probability of selection. Every element is
selected independently of every other element. The
sample is drawn by a random procedure from a
sampling frame.
Example: Lottery system

Systematic Sampling
In systematic sampling, the sample is chosen by
selecting a random starting point and then picking
every ith element in succession from the sampling
frame. The sampling interval, i, is determined by
dividing the population size N by the sample size n
and rounding to the nearest integer.

Stratified sampling
Stratified sampling is a two-step process in which the
population is divided into subpopulations, or strata.
Next, elements are selected from each stratum by a
random procedure, usually SRS.
A major objective of stratified sampling is to increase
sampling efficiency by increasing precision and without
increasing cost.

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 clusters is selected, based on a probability
sampling techniques such as SRS.
A major objective of cluster sampling is to increase
sampling efficiency by decreasing costs.

Stratified and Cluster Sampling
• Stratified
• Population divided into
few subgroups
• Homogeneity within
subgroups
• Heterogeneity between
subgroups
• All subgroups included
• Cluster
• Population divided into
many subgroups
• Heterogeneity within
subgroups
• Homogeneity between
subgroups
• Random selection of
subgroup

8/20/2022 194
Session 11
Determination of Sample Size

Determine the sample size
Sample size refers to the number of elements to be
included in the study.
Determination of sample size depends on several
qualitative and quantitative factors.

Qualitative factors:
• The importance of the decision
• The nature of the research
• The number of variables
• Resource constraints

• Precision level: It is the maximum permissible
difference between the sample statistic and the
population parameter.
• Confidence Interval: The confidence interval is the
range into which the true population parameter will
fall, assuming a given level of confidence.

• Confidence level: The confidence level is the
probability that a confidence interval will include the
population parameter.

Sample Size Determination: Means
Sample Size Determination: Proportions

Field Work

The Nature of Fieldwork
• Fieldworker
– An individual who is responsible for gathering data
in the field.
– Typical fieldwork activities:
• A personal interviewer administering a questionnaire
door to door
• A telephone interviewer calling from a central location
• An observer counting pedestrians in a shopping mall
• Other’s supervising the collection of data

Fieldwork/Data-Collection Process
• Selection of field workers
• Training of field workers
• Supervision of field workers
• Validation of field workers
• Evaluation of field workers

Selection of field workers
• Develop job specification for the project, taking into
account the mode of data collection.
• Decide what characteristics the field workers should
have
• Recruit appropriate individuals

Training of field workers
• Briefing Session
– A training session to ensure that each interviewer is provided with
common information.
• Training Objective
– To ensure that the data collection instrument will be administered in
a uniform fashion by all fieldworkers.
• Training Topics
– Making initial contact with the respondent and secure the interview
– Asking the questions
– Probing
– Recording the responses
– Terminating the interview

Making Initial Contact
• Personal Interviews
– Making opening remarks that will convince the respondent that his or
her cooperation is important.
• Telephone Interviews
– Giving the interviewer’s name personalizes the call.
– Providing the name of the research agency is used to imply that the
caller is trustworthy.
– Providing an accurate estimate of the time helps gain cooperation.
• Internet Surveys
– Respondent may receive an e-mail requesting assistance.

Asking the Questions
• Major Rules for Asking Questions:
1. Ask questions exactly as they are worded in the
questionnaire.
2. Read each question very carefully and clearly.
3. Ask the questions in the specified order.
4. Ask every question specified in the questionnaire.
5. Repeat questions that are misunderstood or
misinterpreted.

Probing
• Probing
– Verbal attempts made by a field-worker when the
respondent must be motivated to communicate
his or her answers more fully.
• Probing Tactics that Enlarge and Clarify:
– Repeating the question
– Using a silent probe
– Repeating the respondent’s reply
– Asking a neutral question

Commonly Used Probes and Their Abbreviations

Recording the Responses
• Rules for recording responses to fixed-alternative questions
vary with the specific questionnaire.
• Rules for recording open-ended answers include:
– Record responses during the interview.
– Use the respondent’s own words.
– Do not summarize or paraphrase the respondent’s answer.
– Include everything that pertains to the question objectives.
– Include all of your probes.
• How answers are recorded can affect researchers’
interpretation of the respondent’s answers.

Terminating the Interview
• How to close the interview is important:
– Fieldworkers should wait to close the interview until they
have secured all pertinent information including
spontaneous comments of the respondent.
– Fieldworkers should answer any respondent questions
concerning the nature and purpose of the study to the
best of his or her ability.
– Avoiding hasty departures is a matter of courtesy.
– It is important to thank the respondent for his or her time
and cooperation as reinterviewing may be required.

Supervision of Fieldworkers
• Sampling Verification
– Verifying that interviews are being conducted
according to the sampling plan rather than with
the sampling units most accessible to the
interviewer.
• Interviewer cheating
– The practice by fieldworkers of filling in fake
answers or falsifying interviews.
• Curb-stoning: a form of interviewer cheating in which
an interviewer makes up the responses instead of
conducting an actual interview.

Validation of Field Work
• Validation by Reinterviewing
– Quality-control procedures in fieldwork intended
to ensure that interviewers are following the
sampling procedures and to determine whether
interviewers are cheating.
– Supervisors call 10 to 25% of the respondent to
inquire whether the fieldworkers actually
conducted the interviews,

Evaluation of the Field Workers
• Evaluation criteria
-cost and time
-response rates
-quality of interviewing
-quality of data

Session 12
Factor Analysis
8/20/2022 Dr. Rajeev Sirohi, LBSIM 214

Exploratory factor analysis . . . is an
interdependence technique whose primary
purpose is to define the underlying structure
among the variables in the analysis.
Exploratory Factor Analysis
Defined

Exploratory Factor Analysis . . .
• Examines the interrelationships among a large
number of variables and then attempts to explain
them in terms of their common underlying
dimensions.
• These common underlying dimensions are referred
to as factors.
• A summarization and data reduction technique that
does not have independent and dependent
variables, but is an interdependence technique in
which all variables are considered simultaneously.
What is Exploratory Factor Analysis?

Application of Factor Analysis
to a Fast-Food Restaurant
Service Quality
Food Quality
Factors
Variables
Waiting Time
Cleanliness
Friendly Employees
Taste
Temperature
Freshness

Factor Analysis Decision Process
Stage 1: Objectives of Factor Analysis
Stage 2: Designing a Factor Analysis
Stage 3: Assumptions in Factor Analysis
Stage 4: Deriving Factors and Assessing Overall Fit
Stage 5: Interpreting the Factors
Stage 6: Validation of Factor Analysis
Stage 7: Additional uses of Factor Analysis Results

Stage 1: Objectives of Factor Analysis
1. Is the objective exploratory or confirmatory?
2. Specify the unit of analysis.
3. Data summarization and/or reduction?
4. Using factor analysis with other techniques.

Types of Factor Analysis
1. Exploratory Factor Analysis (EFA) = is
used to discover the factor structure of a
construct and examine its reliability. It is
data driven.
2. Confirmatory Factor Analysis (CFA) = is
used to confirm the fit of the hypothesized
factor structure to the observed (sample)
data. It is theory driven.

Factor Analysis Outcomes
1. Data summarization = derives underlying
dimensions that, when interpreted and
understood, describe the data in a much
smaller number of concepts than the original
individual variables.
2. Data reduction = extends the process of
data summarization by deriving an empirical
value (factor score or summated scale) for
each dimension (factor) and then substituting
this value for the original values.

Stage 2: Designing a Factor Analysis
Three Basic Decisions:
1. Correlations among variables
2. Variable selection and measurement
issues
3. Sample size

Stage 3: Assumptions in Factor Analysis
1. Conceptual issues.
2. Statistical issues.
3. Overall measures of intercorrelation.

Stage 4: Deriving Factors and Assessing Overall
Fit
• Selecting the factor extraction method –
common factor analysis vs. component
analysis.
• Criteria for the number of factors to
extract.

Extraction Decisions
o Which method?
• Principal Components Analysis
• Common Factor Analysis

Number of Factors?
• A Priori Criterion
• Latent Root Criterion
(eigenvalues)
• Percentage of Variance
• Scree Test Criterion

Eigenvalue Plot for Scree Test
Criterion

Stage 5: Interpreting the Factors
• Estimate the Factor Matrix
• Factor Rotation
• Factor Interpretation
• Respecification of factor model, if needed, may
involve . . .
o Deletion of variables from analysis
o Desire to use a different rotational approach
o Need to extract a different number of factors
o Desire to change method of extraction

Two Rotational Approaches
1. Orthogonal = axes are maintained
at 90 degrees.
2. Oblique = axes are not maintained
at 90 degrees.

Unrotated
Factor II
Unrotated
Factor I
Rotated
Factor I
Rotated Factor II
-1.0 -.50 0 +.50 +1.0
-.50
-1.0
+1.0
+.50
V1
V2
V3
V4
V5
Orthogonal Factor
Rotation

Unrotated
Factor II
Unrotated
Factor I
Oblique
Rotation:
Factor I
Orthogonal Rotation:
Factor II
-1.0 -.50 0 +.50 +1.0
-.50
-1.0
+1.0
+.50
V1
V2
V3
V4
V5
Orthogonal
Rotation: Factor I
Oblique Rotation:
Factor II
Oblique Factor Rotation

Orthogonal Rotation Methods
• Quartimax (simplify rows)
• Varimax (simplify columns)
• Equimax (combination)

Which Factor Loadings Are Significant?
• Customary Criteria = Practical Significance.
• Sample Size & Statistical Significance.

Factor Loading Sample Size Needed
for Significance*
.30 350
.35 250
.40 200
.45 150
.50 120
.55 100
.60 85
.65 70
.70 60
.75 50
*Significance is based on a .05 significance level (a), a power level of 80 percent, and
standard errors assumed to be twice those of conventional correlation coefficients.
Guidelines for Identifying Significant
Factor Loadings Based on Sample Size

Interpreting a Factor Matrix:
1. Examine the factor matrix of
loadings.
2. Identify the highest loading across
all factors for each variable.
3. Assess communalities of the
variables.
4. Label the factors.

Stage 6: Validation of Factor Analysis
• Confirmatory Perspective.
• Assessing Factor Structure Stability.

Stage 7: Additional Uses of Factor
Analysis Results
• Creating Summated Scales
• Computing Factor Scores

Session 13
Multiple Discriminant Analysis

Discriminant analysis . . . is an appropriate technique
when the dependent variable is categorical (nominal or
nonmetric) and the independent variables are metric. The
single dependent variable can have two, three or more
categories.
Discriminant Analysis Defined
Examples:
• Success and failure of a new product/firm
• Gender – Male vs. Female
• Heavy Users vs. Light Users
• Purchasers vs. Non-purchasers
• Good Credit Risk vs. Poor Credit Risk
• Member vs. Non-Member

KitchenAid Survey Results for the Evaluation* of
a New Consumer Product
X3
Style
Group 1
Would purchase 1 8 9 6
2 6 7 5
3 10 6 3
4 9 4 4
5 4 8 2
Group Mean 7.4 6.8 4.0
Group 2
Would not purchase 6 5 4 7
7 3 7 2
8 4 5 5
9 2 4 3
10 2 2 2
Group Mean 3.2 4.4 3.8
Difference between group means 4.2 2.4 0.2
Purchase Intention Subject
Number
X1
Durability
X2
Performance
*Evaluations made on a 0 (very poor) to 10 (excellent) rating scale.

Discriminant Analysis Decision Process
Stage 1: Objectives of Discriminant Analysis
Stage 2: Research Design for Discriminant Analysis
Stage 3: Assumptions of Discriminant Analysis
Stage 4: Estimation of the Discriminant Model and
Assessing Overall Fit
Stage 5: Interpretation of the Results
Stage 6: Validation of the Results

Stage 1: Objectives of Discriminant Analysis
1. Determine if statistically significant differences
exist between the two (or more) a priori
defined groups.
2. Identify the relative importance of each of the
independent variables in predicting group
membership.
3. Develop procedures for classifying objects
(individuals, firms, products, etc.) into groups,
and then examining the predictive accuracy
(hit ratio) of the discriminant function to see if it
is acceptable (> 25% increase).

• Selection of dependent and
independent variables.
• Sample size (total & per variable).
• Sample division for validation.
Stage 2: Research Design for Discriminant Analysis

Converting Metric Variables to Nonmetric
• Most common approach = to use the metric scale
responses to develop nonmetric categories. For
example, use a question asking the typical number
of soft drinks consumed per day and develop a
three-category variable of 0 drinks for non-users, 1
– 5 for light users, and 5 or more for heavy users.
• Polar extremes approach = compares only the
extreme two groups and excludes the middle
group(s).

Key Assumptions
• Multivariate normality of the independent variables.
• Equal variance and covariance for the groups
(homoscedasticity).

Other Assumptions
• Minimal multicollinearity among
independent variables.
• Group sample sizes relatively equal.
• Linear relationships.
• Elimination of outliers.

Stage 4: Estimation of the Discriminant Model and
Assessing Overall Fit
Selecting An Estimation Method . . .
1. Simultaneous Estimation – all
independent variables are considered
concurrently.
2. Stepwise Estimation – independent
variables are entered into the
discriminant function one at a time.

Assessing Overall Model Fit
• Calculating discriminant Z scores
for each observation,
• Evaluating group differences on the
discriminant Z scores, and
• Assessing group membership
prediction accuracy. Construct
classification matrices.

Stage 5: Interpretation of the Results
Three Methods . . .
1. Standardized discriminant weights,
2. Discriminant loadings (structure
correlations), and
3. Partial F values.

Stage 6: Validation of the Results
• Utilizing a Holdout Sample
• Cross-Validation

8/20/2022 251
Session 14
Communicating Research Results: Report
Generation, Oral Presentation and
Follow-up

Research Report
• Research Report
– An oral presentation or written statement of
research results, strategic recommendations,
and/or other conclusions to a specific audience.
– Directed to the client or management who
initiated the research.
– Usually supported by a formal presentation
delivered in person or via the Internet.

SIGNIFICANCE OF REPORT WRITING
The purpose of research is not well served unless the
findings are made known to others. Research results
must invariably enter the general store of
knowledge.

LAYOUT OF THE RESEARCH REPORT
The layout of the report means as to what the research
report should contain. A comprehensive layout of the
research report should comprise
(A) preliminary pages;
(B) the main text; and
(C) the end matter.

(A) Preliminary Pages
• Title page
• Letter of Transmittal
– Releases or delivers the report to the recipient in
formal way.
• Letter of Authorization
– Approves the project, details who has
responsibility for it, and describes resources
available to support it.
• Acknowledgements
• Table of contents
• List of tables and list of figures
• Executive summary

(B) Main Text
Each main section of the report should begin on a new page. The
main text of the report should have the following sections:
(i) Introduction (back ground of the topic, importance of the study)
(ii) Review of Literature
(iii) Objectives of research
(iv) Research Methodology (research design, sample design, data
collection and field work, analysis)
(v) Data Analysis and Interpretation (tables, charts, and an
organized narrative.
(vi) Finding and Recommendations
(vii) Conclusion
(viii)Limitations and Future Research

Using Charts Effectively
• Charts
– Translate numerical information into visual form
so that relationships may be easily grasped.
– Chart elements
• Figure number
• Title
• Explanatory legends
• Source and footnotes
– Charts are subject to distortion.

EXHIBIT 25.10 Distortion by Alternating Scales

EXHIBIT 25.11 Distortion from Treating Unequal Time Intervals as Equal
Source: Adapted with permission from Mary Eleanor Spear, Practical Charting Techniques (New York; McGraw-Hill, 1969), p. 57.

Using Charts Effectively (cont’d)
• Pie Charts
– Show the composition of some total quantity at a
particular time.
– Each angle, or “slice,” is proportional to its
percentage of the whole.

EXHIBIT 25.13 Pie Charts

• Line Graphs
– Show the relationship of one variable to another.
– The dependent variable generally is shown on the
vertical axis, and the independent variable on the
horizontal axis.
• Simple line graph
• Multiple-line graph
• Stratum chart

EXHIBIT 25.14 Simple Line Graph

EXHIBIT 25.15 Multiple-Line Graph

EXHIBIT 25.16 Stratum Chart

• Bar Charts
– Show changes in the value of a dependent
variable (plotted on the vertical axis) at discrete
intervals of the independent variable (on the
horizontal axis).
– Types:
• Subdivided-bar chart
• Multiple-bar chart

EXHIBIT 25.17 Simple Bar Chart

EXHIBIT 25.18 Subdivided Bar Chart

EXHIBIT 25.19 Multiple-Bar Chart

(C) End Matter
At the end of the report, appendices should be enlisted in
respect of all technical data such as questionnaires, sample
information, mathematical derivations and the like ones.
Bibliography of sources consulted should also be given. Index
(an alphabetical listing of names, places and topics along with
the numbers of the pages in a book or report on which they
are mentioned or discussed) should invariably be given at the
end of the report. The value of index lies in the fact that it
works as a guide to the reader for the contents in the report.

Preparation of the final bibliography
The bibliography, which is generally appended to the research
report, is a list of books in some way pertinent to the research
which has been done. It should contain all those works which
the researcher has consulted. The bibliography should be
arranged alphabetically and may be divided into two parts;
the first part may contain the names of books and pamphlets,
and the second part may contain the names of magazine and
newspaper articles.

For books and pamphlets the order may be as under:
1. Name of author, last name first.
2. Title, underlined to indicate italics.
3. Place, publisher, and date of publication.
4. Number of volumes.
Example
Kothari, C.R., Quantitative Techniques, New Delhi, Vikas
Publishing House Pvt. Ltd., 1978.

For magazines and newspapers the order may be as under:
1. Name of the author, last name first.
2. Title of article, in quotation marks.
3. Name of periodical, underlined to indicate italics.
4. The volume or volume and number.
5. The date of the issue.
6. The pagination.
Example
Robert V. Roosa, “Coping with Short-term International Money
Flows”, The Banker, London, September, 1971, p. 995.

Preparation of the index
At the end of the report, an index should invariably be given, the
value of which lies in the fact that it acts as a good guide, to
the reader. Index may be prepared both as subject index and
as author index. The former gives the names of the subject-
topics or concepts along with the number of pages on which
they have appeared or discussed in the report, whereas the
latter gives the similar information regarding the names of
authors. The index should always be arranged alphabetically.

PRECAUTIONS FOR WRITING RESEARCH REPORTS
1. Length of the report: Long enough to cover the subject
but short enough to maintain interest.
3. Abstract terminology and technical jargon should be
avoided in a research report.
4. Charts, graphs and the statistical tables may be used for
the various results in the main report.
5. The reports should be free from grammatical mistakes.
whether typed or printed.

PRECAUTIONS FOR WRITING RESEARCH REPORTS
6. A research report should show originality. It must
contribute to the solution of a problem and must add
to the store of knowledge.
7. Bibliography of sources consulted must necessarily be
given.
8. Report must be attractive in appearance, neat and
clean, whether typed or printed.

The Oral Presentation
• Oral Presentation
– A spoken summary of the major findings,
conclusions, and recommendations, given to
clients or line managers to provide them with the
opportunity to clarify any ambiguous issues by
asking questions.
– Keys to effective presentation:
• Preparation (rehearsal)
• Adapting to the audience
• Not lecturing or reading to the audience
• Use graphic aids effectively
• Speaking effectively and convincingly

Reports on the Internet
• An easy way to share data is to make
executive summaries and reports available on
a company intranet.
• Can use the Internet to:
– Design questionnaires
– Administer surveys
– Analyze data
– Share the results

The Research Follow-Up
• Research Follow-up
– Recontacting decision makers and/or clients after
they have had a chance to read over a research
report in order to determine whether additional
information or clarification is necessary.

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