Business Research Methodology Lectures

BUSINESS RESEARCH
METHODOLOGY LECTURES
BY
NTANGSI MAX MEMFIH
Research Methods Lectures by Ntangsi 1

Topic 1: INTRODUCTION
Session Objectives
To understand the meaning of research,
To understand the meaning of research
Methodology,
To understand the objectives of research
To understand the characteristics of research
To understand the basic steps of conducting
research - Problem Solving Approach .

Basic Concepts or Definitions
 Definition of Research
 Definition of Methodology
 Definition of Research Methodology
 The Aims of Research
Characteristics of research
 Basic Steps to Conduct Research
3Research Methods Lecture by Ntangsi Max

What is Research?
Research is:
“…the systematic process of collecting
and analyzing data (information) in
order to increase our understanding of
the phenomenon on which we are
concerned or interested”
In short, it is the search for knowledge
through objective and systematic
method of finding solutions to problems.
4Research Methods Lecture by Ntangsi

More Understanding of Research
Research is a careful and systematic process
of inquiry to find answers to problems of
interest.
Research include: use of facts, use of
theories, data (facts) analysis, sampling,
doing an experiment, going to library to read
up on a topic
To do ‘research’ is to investigate the problem
systematically and thoroughly
Goal of research is to solve ‘problem’ of
interest

Characteristics of Research
1. Originates with a question or a problem.
2. Requires clear articulation of a goal.
3. Follows a specific plan or procedure.
4. Often divides main problem into sub problems.
5. Guided by specific problem, question, or
hypothesis.
6. Accepts certain critical assumptions.
7. Requires collection and interpretation of data.
8. Cyclical (helical) in nature - Repetitive.

The Aims of Research
 To understand a phenomenon better so as to find out
the truth about it
 To describe a phenomenon as it is
 To predict about “something” in the future
 To explain solutions to problems
 To interpret what is being investigated and to make
recommendations
 To Discover new things – innovation.
 Though each study has its own specific purpose, this
may fall under the following broad groupings:
 To gain familiarity with a phenomenon or to achieve new
insights into it - exploratory or formulative
 To portray accurately the characteristics of a particular
individual, situation or a group - descriptive
 To determine the frequency with which something
occurs – diagnostic, etc.

Motivation for Research
What makes people to undertake research?
 Desire to get additional academic or professional
qualifications along with consequential benefits,
 Desire to face the challenge in solving the societal
problems - be of service to society,
 Desire to get intellectual joy of doing some creative
work,
 Desire to get respectability,
 Desire to create additional knowledge or new things,
 Directives of organizations or government,
 Employment conditions,
 Curiosity about new things,
 Desire to understand causal relationships,
 Social thinking and awakening, etc.
Research Methods Lecture by Ntangsi 8

Types of Research
Descriptive vs. Analytical
Descriptive research includes surveys and fact-
finding enquiries of different kinds - Ex post facto
research.
 The major purpose of descriptive research is to
describe the state of affairs as it exists at present.
 The main characteristic of this method is that the
researcher has no control over the variables; he can
only report what has happened or what is happening.
 The methods used in descriptive research are survey
methods
 Analytical research on the other hand uses facts
or information available, and analyze these to
make a critical evaluation of the situation.

Types of Research Cont'd
Applied vs. Fundamental
 Applied research (Action Research) aims at finding
solutions for an immediate problem facing a society or
an organization – Development focused.
 Fundamental research is mainly concerned with
generalizations and with the formulation of a theory.
“Gathering knowledge for knowledge’s sake is termed
‘pure’ or ‘basic’ research.
Quantitative vs. Qualitative
 Quantitative research is based on the measurement of
quantity or amount. It is applicable to phenomena that
can be expressed in terms of quantity.
 Qualitative research, on the other hand, is concerned
with qualitative phenomenon, i.e., phenomena relating to
or involving quality or kind.

Types of Research Cont'd
Conceptual vs. Empirical
 Conceptual research is that related to some abstract
idea(s) or theory. It is generally used by philosophers
and thinkers to develop new concepts or to reinterpret
existing ones.
 Empirical research relies on experience or observation
alone, often without due regard for system and theory. It
is data-based research, coming up with conclusions
which are capable of being verified by observation or
experiment.
 Other Types of Researches include one-time (cross
sectional) research or longitudinal research, field-
setting research or laboratory research, clinical or
diagnostic research, Historical research, etc.
The above research types gives rise to research
approaches

Scientific Methods
“Methods” means way
Methodology is the discipline of scientific
procedures .
Methodology is therefore about;
A formalized approach to conduct research
A series of steps and deliverables
Research Methodology in Business is
“A collection of methods, procedures,
techniques, tools and documentations/aids
which help the researchers in their eﬀorts to
conduct a research in Business”

Research Methodology Vs. Research
Method
Research Methodology:
 Conceptual frameworks and assumptions
used to inform research
 Elaboration of research methods
Research Method:
 Research techniques or procedures used to
gather and analyses data
 A Research method is therefore a subset of
research methodology

Research Methodology Elaborated
 A research methodology will consist of phases, sub‐
phases, which will guide the researchers in their choice of
the methods, techniques, procedures, tools, etc., that might
be appropriate at each stage of the research and also help
them plan, manage, control and evaluate the progress of
research.
 A research methodology represents a way to develop
research systematically.
 A research methodology represents a way to do scientiﬁc
inquiry.
 A research methodology should have a sound
theoretical basis.
 A research methodology should be focused (a plan)
 It leads to a successful research.

Why Methodology?
It will make you better able to understand and
utilize scientific information in both your
personal life and your work.
 It will make you a more literate and cultured
person.
It provides you some insight not only into
particular scientific findings but also into the
general nature of science as a human activity.
It helps you to successfully carry out the
research in a coordinated fashion 15Research Methods Lecture by Ntangsi

Nature of Research in Business
 Business Research requires experimental design as
well as theoretical (basic) research
 Hence, we need to have a methodology in order to
conduct business research
 Scientific approach: new knowledge, theory
 Business Research requires system multiple
Perspectives
 Hence, we need to have a methodology in order to
capture diversity.
 Data requirements is also diversified and quantitative and
qualitative data are useful
 Business research deals with people and thus
uncertainties that are characteristic of human beings.
This requires a well defined Methodology.

The Problem Solving Approach
1 - PROBLEM IDENTIFICATION
2 - PROBLEM DEFINITION
3 - IDENTIFYING VARIABLES OF INTEREST
5 – CONSTRUCTION OF RELEVANT MODELS
6 – COLLECTION OF RELEVANT DATA
7 – ANALYSIS OF DATA
8 – INTERPRETATION OF RESULTS
4 - QUANTIFICATION OF THE VARIABLES
9 – DRAWING RELEVANT
INFERENCES/RECOMMENDATIONS
10 – TAKING ACTION
11 – TAKING RESPONSIBILITIES

Topic 2: Scientific Inquiry
Session Objectives
To understand the steps in Scientiﬁc
Inquiries
To understand the characteristics of
Scientiﬁc Methods
To understand the logical thinking in
Research
To understand various types of Researches
To understand various research
approaches

Session Agenda
Meaning of Scientiﬁc Inquiry
Model of Scientiﬁc Inquiry
Inductive and Deductive Logical
Thinking
Types of Research Methods
Types of Research Approaches

What is Scientific Inquiry?
 Scientific inquiry is a term that encompasses a
variety of techniques that scientists use to explore
the natural world and propose explanations based on
the evidence they find.
 The objective of scientific inquiry is to find and to
characterize the patterns as resulted from the
exploration.
 Scientific inquiry is founded on experiment and
observations as opposed to purely rational or
isolated logical thought.
 Scientific Inquiry can enrich our understanding of
science

Why Scientiﬁc Inquiry?
It will make us more knowledgeable about
something.
You will be able to explain about something
more thorough.
It will make us a more literate and cultured
persons.
It will provide us with more ideas.
It will enable us to take more informed
Decisions.

Characteristics of Scientific Inquiry
Based on facts
Objective Consideration
Analytical
Quantitative in Nature
Deductive Logic-Hypothesis
Inductive Logic-Generalization
Dynamic with time

Activities in Scientiﬁc Inquiry
Making observations
Posing questions
Finding out what is already known
Planning investigations
Reviewing past knowledge in light of actual
evidence
Using tools to gather, analyze, and interpret
data
Proposing explanations
Communicating the results.

Models of Scientific Inquiry
Classical model
The classical model of scientific inquiry derives from Aristotle, who
distinguished the forms of approximate and exact reasoning, set out
the threefold scheme of adductive, deductive, and inductive inference
and also treated the compound forms such as reasoning by analogy.
Pragmatic model
Charles Peirce considered scientific inquiry to be a species of the genus
inquiry, which he defined as any means of fixing belief, that is, any
means of arriving at a settled opinion on a matter in question.
He observed that inquiry in general begins with a state of uncertainty
and moves toward a state of certainty, sufficient at least to terminate
the inquiry for the 5me being.

Model of Scientiﬁc of Inquiry
State General Problem
Conduct Literature Search
State Specific Problem
Design Methodology
Gather Data
Analyze Data
Report Results
Refine Hypotheses

Another Model…..
Problem Statement
Organize Critical Thinking Framework
Organize Premises
Hypothesis Formulation
Testing Hypothesis
Draw Conclusion

Output of Each Step
 State General Problem
 Statement that stated general problems
 Example: Will the universe expand forever?
– Exercise: State at least three general problems on your own
 Conduct Literature Search
 List all related literatures to the problems stated
 Underline all theories, techniques, methods, ﬁndings and so
forth that others have found
 Critically analyze all the weaknesses, strengths, similarities,
dissimilarities among those theories, techniques,
ﬁndings above.
 Summarize all those literatures (make annotated bibliographies)

Output of Each Step
 State Specific Problem
 Statement of general problem to specific problem
– Example: What are the factors that cause the universe
expanded?
– Exercise: State at least two specific problems that can
be derived
from the above exercise
Design Methodology
 List all steps to be taken in order to answer those stated
problems
 Establish the seZng of experiment
 Provide all necessary means, tools, instruments
 Define the object, variables, etc

Output of Each Step
Gather Data
–Organize data in tables, graphics
Analyze Data
– Interpret the organized, and processed data
Report the Results

Basic Skills of Scientiﬁc Inquiry
Observing
Classifying and sequencing
Communicating
Measuring
Predicting
Hypothesizing
Inferring
Deﬁning, controlling, and manipulating variable in
experimentation
Designing, constructing and interpreting models
Interpreting, analyzing and evaluating data

Uses of Scientiﬁc Inquiry
Make connections with real world situations
To encourage more active problem solving
approach to learning and thinking
To apply mathematical skills
Review what is already known in light of
experimental evidence
Propose answers, explanations and predictions
Use tools to gather, analyze and interpret data

Exercises Your Thought
Develop a scientiﬁc model of your own
– Post deliverables of each step of the model
Categorized the scientiﬁc model into a research
method
Give examples of deductive and inductive logic
or research

TOPIC 3: PROBLEM IDENTIFICATION
Session Objectives
To understand the ﬁrst step of conducting
research - stating the problem
 To understand what a research problem is,
To be able to state main research problems
To be able to identify speciﬁc research problems
To be able to derive research questions
To be able to identify variables involved in a
research
To be able to derive research objectives
To be able to construct hypotheses

The Problem Solving Approach/Research Process
1. Problem Identification
2. Problem Definition/Formulation
3. Identification of Variables of Interests
4. Quantification of the variables
5. Construction of Mathematical Models
6. Collection of Data
7. Analysis of Data
8. Interpretation of Results
9. Drawing relevant
Inferences/Recommendations
10. Implementation (Taking Action) and
11.Taking Responsibilities 34Research Methods Lecture by Ntangsi

Problem Identification
Determine a well defined general problem
 Sources: observation, research articles, scientific
discussions, experience, etc.
 Point of interest: phenomena, theories, previous
research results, etc.
Exercise your thought to express the problems
Write them as quickly and as clearly as possible
Be ready, that some (may be all) of your general
problems are not researchable
 Conduct literature search
 Consult experts 35Research Methods Lecture by Ntangsi Max

Problem Formulation
This involves;
Identification of Research Problem
A Problem exist when what is differs
from what ought to be,
Identification of the Scope of Research
Identification of Research Questions
Identification of Research Objectives
Stating of Hypothesis
 1. Statistical Hypothesis
 2. Hypothetical Statement 36Research Methods Lecture by Ntangsi

Conditions Under which Problems Exist
There must be an entity to which the problem
can be attributed (individual, society or
organization, geographical area, etc),
There must be at least two courses of action,
to be pursued,
There must be at least two possible outcomes
of which one should be preferred,
The courses of action available must provides
some chance of obtaining the objective,
Problem exist only if the best course of action
is not known. 37Research Methods Lecture by Ntangsi

Components of a Research Problem
There must be an individual or a group which
has some difficulty or the problem.
There must be some objective(s) to be attained,
There must be alternative means for obtaining
the objective(s)
There must be some doubt in the mind of a
researcher with regard to the best alternative,
There must be some environment(s) to which
the difficulty pertains.

Factors Affecting Complexity of Problem(s)
The environment may change affecting the
efficiencies of the courses of action or the
values of the outcomes;
The number of alternative courses of action
may be very large;
Externalities - Persons not involved in making
the decision may be affected by it and react to it
favourably or unfavourably,
Available resources to use in addressing the
problem(s),
Knowledge level of the researcher or team, etc.

Sources of Res. Problems in Businesses
Performance Level of the company,
Customer Complaints,
Conversing with company stakeholders like
employees, shareholders, suppliers, etc.
Observation of abnormal happenings in the firm,
Activities deviating from the Business/ Strategic
plan,
Competitors excelling at the expense of the firm,
Reading of relevant reports of the firm,
Personal knowledge of the firm in respect of the
industry,
Experiences from similar firms, etc.

SELECTING THE PROBLEM
The research problem chosen for study must be
carefully selected.
 Avoid topics which have been overdone,
 Controversial topics should also be avoided,
 Too narrow or too vague problems should be avoided.
 Selected topics you are familiar with,
 Select topics that are feasible so that the related
research material are within one’s reach;
 Select important topics in the circumstances,
 Consider the resources available (time, money, etc)
 Select topics which are useful and will contribute to
solving existing problems or adding to knowledge,
 The selection of a problem must be preceded by a
preliminary study 41Research Methods Lecture by Ntangsi

Questions to be asked before final Selection
Whether you are well equipped in terms of the
background to carry out the research? – the
knowledge required, your area of interests,
Whether the study falls within the budget you can
afford as well as the time available to you for the
study?
Whether the necessary cooperation can be
obtained from those who must participate in
research as subjects? – Can data be obtained?
Is the study going to be useful to the researcher/
company in particular and to society in general?
How long will the research take and how much will
it cost? etc.

NECESSITY OF DEFINING THE PROBLEM CLEARLY
“A problem clearly stated is a problem half
solved” This statement signifies the need for
defining a research problem properly and clearly.
The problem to be investigated must be defined
unambiguously.
Questions like: What data are to be collected?
What characteristics of data are relevant and need
to be studied? What relations are to be explored?
What techniques are to be used for the purpose?
and similar other questions will have straight
answers once the problem is well defined.

TECHNIQUES INVOLVED IN DEFINING A PROBLEM
 Defining a research problem properly and
clearly is a crucial part of a research study and
must in no case be done hurriedly. Useful
Steps involves include;
statement of the problem in a general way;
understanding the nature of the problem;
surveying the available literature;
developing the ideas through discussions;
Rephrasing the research problem into a
working proposition.

Defining the Research Problem
Technical terms and words or phrases, with special
meanings used in the statement of the problem,
should be clearly refined.
Basic assumptions or postulates (if any) relating to
the research problem should be clearly stated.
A straight forward statement of the value of the
investigation (i.e., the criteria for the selection of
the problem) should be provided.
The suitability of the time-period and the sources
of data available must also be considered by the
researcher in defining the problem.
The scope of the investigation or the limits within
which the problem is to be studied must be
mentioned explicitly in defining a research
problem. 45Research Methods Lecture by Ntangsi

Research Problems/Questions
 Research needs both problems and questions
 Qualities of good research questions:
 The Research Questions should be clear, straightforward
and easily understood by others
 The Research Questions states the relationship between
two or more variables.
 The variables mentioned in the Research Questions
should be measurable – qualitatively and quantitatively.
 The answers to the Research Questions are not
immediately obvious.
 The Research Questions indicates the method that is to
be adopted, i.e. the data collection techniques
 The Research Questions can be answered in the time
available to you.
 The Research Questions can be answered with the
resources available to you.

Determine Research Objectives
 Make sure you have a strong reason why such research
is worth doing
 Study the impact, effects, role?
 Study the usage?
 Study features, Etc.
 Research objectives should reﬂect the solution of the
problem/questions
– If you can not state the problem/questions, then,
you can not state the objectives
 Build your Objectives based on facts (previous studies,
existing problems, the aims of research, etc.)
 Main and specific Objectives
 The objectives should relate to the research questions.

Qualities of good research Objectives:
• They should be categorical i.e each should start with to….
• They should be linked to the research problem/questions
– derived from research questions
 The Research objectives should be clear, straightforward and
easily understood by others
 The Research objectives states the relationship between two or
more variables.
 The variables mentioned in the Research objectives should be
measurable – qualitatively or quantitatively.
 The answer to the Research objectives is not immediately
obvious.
 The Research objectives indicates the method that is to be
adopted, i.e. the data collection techniques
 The Research objectives can be answered in the time available to
you.
 The Research objectives can be answered with the resources
available to you. 48Research Methods Lecture by Ntangsi

Identification of Variables of Interest
A variable is a property that can take on many values
e.g. Age is a variable. It can take on many different
values, such as 18, 49, 72, and so on, Gender is a
variable. It can take on two different values, either male
or female, Place (in a race) is another variable. It can
take on values such as 1st place, 2nd place, 3rd place,
and so on.
Two kinds of variables: Quantitative Variables, and
Qualitative/Categorical Variables:
 A quantitative variable is count and measured
numerically. There are two further kinds of quantitative
variables: Discrete and Continuous
 Qualitative/Categorical variables are non count or
measured data but allows for classification based on
some precise characteristics.

Stating of Hypothesis
 Declarative statements linking variable(s) to another(s)
 Basically, there are two types of hypotheses:
– Hypothetical statement
– Statistical hypothesis
 Hypothetical statement does not use
statistical analysis and thus not useful in research
 Statistical hypothesis uses statistical analysis.
 The Hypotheses should be linked to the research
objectives.
 If possible, each specific objective could give rise to a
hypothesis.
 Once stated in a study must be tested,

Qualities of Good Hypothesis
Power of Prediction
Closest to Observable things
Simplicity
Clarity – conceptually and practically
Relate variables to others
Stated in null form
Testable empirically
Relevant to the problem
Specific to a particular problem
Relevant to available techniques
Useful for new discoveries
Consistency and harmony, etc.

Questions
Bring an Illustration on problem Definition.
Identify some specific problems related to your
organization or any other structure
Build arguments why such specific problems are
worth to research.
State these arguments as research problems
Generate the Objectives
Express your experience in stating hypothesis
– Hypothetical statements
– Statistical hypotheses

Topic 4: How to Review Literature
Session Objectives
 To understand how to search relevant literatures.
 To understand the objectives of reviewing literature
 To understand the processes of reviewing literature
 To understand the components of literature to be
reviewed.
 To understand the state‐of‐the‐art literature related to
the problem statement.
 To understand how to structure the literature review
section.
 To understand various referencing methods, etc.

Overview of Previous Sessions
The statement of general problem(s) as the
basis to ﬁnd related literature.
 At this state, the nature of the problem(s) still
shaky and blurred.
Reviewing literature will enhance the statement
of the problem(s).
 Literatures reviewed need to have logical connection
to the problem statement.
Finding and reviewing related literatures are an
art as well a scientiﬁc acts.

What is a Literature Review?
It is a survey of scholarly articles, books and
other sources (e.g. dissertations, journals,
conference proceedings) relevant to a
particular issue, area of research, or theory
• Textbook, magazine, Bulletin are suggested
It is providing a description, summary, and
critical evaluation of each work (each
research article)
The purpose is to offer an overview of
significant literature published on a topic
(overview the state-of-the-art).

Definition Cont’d
 A Literature review is a body of text that aims to review the
critical points of current knowledge on a particular topic.
 Most often associated with science‐oriented literature, such as
a thesis, the literature review usually precedes a research
proposal, methodology and results section.
 Its ultimate goal is to bring the reader up to date with current
literature on a topic and forms the basis for another goal, such
as the justiﬁcation for future research in the area.
 A good literature review is characterized by: a logical ﬂow
of ideas; current and relevant references with consistent,
appropriate referencing style; proper use of terminology;
and an unbiased and comprehensive view of the previous
research on the topic.

Deﬁnition Cont’d
 According to Cooper (1988) "a literature review uses
as its database reports of primary or original
scholarship, and does not report new primary
scholarship itself.
 The primary reports used in the literature may be
verbal (oral Literature), but in the vast majority of
cases reports are written documents.
 The types of scholarship may be empirical,
theoretical, critical/analytic, or methodological in
nature. A literature review seeks to describe,
summarize, evaluate, clarify and/or integrate the
content of primary reports".

How to Find Relevant Literatures?
Search with the key‐word of the research topic.
– Use broader key‐word (term) if the documents
retrieved are few or none.
– Use narrower key‐words if the documents retrieved are
too much.
– Use synonyms or related terms to enhance the search
Pick the most recent and related articles or
books to start with.
Start looking for another related articles through:
– New search terms found in the related articles
– List of references in the chosen article

The Objectives of Reviewing Literature
 Places each work (research article) in the context of its
contribution to the understanding of the subject under review
 Describes the relationship of each work to the others
under consideration
 Identifies new ways to interpret, and shed light on any gaps in
previous research
 Resolves conﬂicts amongst seemingly contradictory studies
 Identifies areas of prior scholarship to prevent duplication of
eﬀorts
 Points the way forward for further research
 Places one's original work (like theses or dissertations) in the
context of existing literature
 Provides a base for the development of a methodology, etc

Why do a Literature Review?
 To identify gaps in the existing works/literature
 To avoid reinventing the wheel (at the very least this will
save time and it can stop you from making the same
mistakes as others)
 To identify methods that could be relevant to your project
 To carry on from where others have already reached
(reviewing the literature enables you to build
on the platform of existing knowledge and ideas)
 To identify other people working in the same area (a
researcher network is a valuable resource)
 To increase your breadth of knowledge in the subject area
 To be able to identify a research problem,
 To see the level of work done in a particular aspect of
study,

Why Review Literature Cont’d
To fine tune your research problem,
To identify similar works in your area,
To provide the intellectual context for your own
work, enabling you to position your research
relative to other works,
To identify opposing views
To put your work into perspective
To demonstrate that you can access previous
work in an area
To identify information and ideas that may be
relevant to your research

Elements of Literature to Review
 The concepts involved in the research area (topic),
 An overview of the subject, issue or theory under consideration
along with the objectives of the literature review,
 Division of works under review into categories (e.g. those
in support of a particular position, those against, and
those oﬀering alternative ideas entirely)
 Explanation of how each work is similar to and how it varies
from the others,
 The methodologies used in addressing similar problems,
 Findings arrived at by similar studies,
 Conclusions as to which pieces are best considered in their
arguments, are most convincing of their opinions, and make
the greatest contribution to the understanding and development
of their area of research,

How to Review Literature
 Compare: Try to find the similarities among literatures
 Explain how each work is similar to the others.
 Contrast: Try to find the differences among literatures
 Explain how each work differs from the others.
 Criticize: put your own opinion on what is written in
the literature.
 Criticize the strength and weakness of the research
 Synthesize: combine several literatures into an idea
 Summarize: restate the article or research with your
own words in a concise way

Where to Place Your Literature Review?
A literature review constitutes an essential chapter
of a thesis or dissertation,
Usually, it is placed in Chapter 2 of your thesis or
dissertation,
Where it is not to be considered as a chapter, it
should logically be connected to research
problems, research methodology, analysis and
conclusions.
In business reports, literature review may be
placed in chapter one as part of the problematic.
However; to make it very visible in a research, it
should be placed in chapter two.

Points to Consider When Reviewing
 Authority - What are the writer's credentials? Are the
author's arguments supported by evidence (e.g. primary,
historical material, case studies, narratives, statistics, recent
scientific findings)?
 Objectivity - Is the author's perspective even‐handed
or prejudicial? Is contrary data considered or is certain pertinent
information ignored to prove the author's point?
 Persuasiveness - Which of the author's theses/ideas/
findings are most/least convincing?
 Value-Are the author's arguments and conclusions convincing?
 Does the work ultimately contribute in any significant way to an
understanding of the subject?
 Historical versus contemporary issues,
 Methodological issues versus results, etc.

Points to Discuss in Literature Review
What is the problem and why is it important?
Is the problem clearly defined?
Try to state the problem as simply as you can
Is the research methodology well stated?
How’s the data being created and manipulated?
Is the manipulated data sufficiently interpreted?
What is the contribution of the study?
Is the conclusion related to the problems?
Is the evidence sufficient enough to support
conclusion? Etc.

The Structure of a Literature Review Section
Three Issues are to be addressed;
Conceptual Issues/Framework,
 Various concepts involved in the topic are
defined
Theoretical Issues/Framework
 Various theoretical issues raised to provide an
analytical framework and
Empirical Issues/Framework
 Findings of previous works reviewed.

Referencing in Scientific Writing
What is referencing?
 It is a method used to demonstrate to your readers that you
have conducted a thorough and appropriate literature review.
 It serves the purpose of accurately acknowledging other
people's work and ideas which you have used in writing your
own work,
Why do referencing?
 Accurate referencing is commensurate with good academic
and professional practice and enhances the presentation of
your work: it shows that your writing is based on knowledge
and informed by appropriate academic and professional
reading. It avoids plagiarism.
 It also ensures that anyone reading your work can trace the
sources you have used in the development of your work, and
give you credit for your research efforts and quality – guides
others.

Referencing styles
There are several different styles of referencing:
AMA (American Medical Association)
APA (American Psychological Association)
MLA (Modern Language Association of America)
AGLC (Australian Guide to Legal Citation)
CSE/CBE (Council of Science Editors/Council of
Biology Editors)
Oxford Style
Harvard Style
Chicago Style
Vancouver Style, etc.

Referencing styles Cont‘d
Each style has its own rules for properly citing
sources.
Author-date styles (e.g. APA, MLA, and Harvard)
put the author's name inside the text of the
document.
Documentary-note styles (e.g. Chicago and
Oxford) put the author's name in a footnote at the
bottom of each page, or in an endnote at the end
of the write up
All of the most common styles list every source
used in a document at the end, in a reference list
or bibliography

Referencing styles Cont‘d
 The styles differ in format. For example, an APA in-text
citation incorporates the author's name, the year of
publication, and sometimes the page number, separated by a
comma: (Lazar, 2006, p. 52)
 An MLA in-text citation, on the other hand, does not include
the year or commas: (Lazar 52).
Where to Use Which?
 APA style is commonly used in Education, Business, and
some Social Sciences and Humanities disciplines.
 MLA style is often used in English and Media Studies.
 Oxford style is often used in History, Philosophy, and
Classics.
 Harvard and Chicago styles are used by most individual
disciplines.
 The APA and Harvard styles should be used for MBA
Dissertations in UB and general business studies.

Topic 5: RESEARCH METHODOLOGY AND PROPOSAL
Objectives of Session
 To understand what a research methodology is all about;
 To understand the uses of a research methodology in
scientific work;
 To understand how to develop a research methodology;
 Understand the structure and content of a research
methodology
 Understand what a research proposal is all about,
 The usefulness of a research proposal,
 Why prepare research proposals,
 The language and tenses used in research proposals,
 The structure of research proposals,
 When to prepare research proposals,
 Guidelines on costing a research.

Research Methodology - Meaning
 “Research Methodology” implies more than simply the
methods you intend to use to collect and analyze data.
 It is often necessary to include a consideration of the
concepts and theories which underlie the methods.
 The methods should be described in enough detail for
the study to be replicated, or at least repeated in a
similar way in another situation.
 Every stage should be explained and justified with
clear reasons for the choice of your particular methods
and materials.
 It specifies the area of study showing clearly the
relevant characteristics of the case study.
 It shows the sources of data and the methods that will
be used in collecting various types of data

Meaning Cont'd
 It specifies the type of variables on which data will be
collected
 It shows the tools that will be used in analyzing data
and how the results will be presented in the study.
 It shows the limitations of proposed data and
analytical tools
 It indicates various professional considerations
(Research ethics) that are involved in a study.
 It thus shows the approach and design that will be
adopted in undertaking a study.
 It also provides a foundation on which the research
process is built.
 It shows the limitations of data and tools.
 It therefore directs the course of the study.

Research Methodology - Usefulness
It helps in providing answers to the following questions;
 How is the study area like-what are the characteristics of
the study area?
 From where will data for the study come from?
 What are the variables on which data will be collected?
 What methods will be used in collecting relevant data?
 What statistical and/or mathematical tools will be used in
analyzing data?
 How will the hypotheses be tested?
 What are the limitations of the data that will be collected
and the tools that will be used for analysis?
 What are the ethical issues that will come into play
during the study?

Research Methodology - Structure
 Background to Study Area
 Data Collection
 Sources of data
 Methods of data collection
 Variables on which data is collected
 Analytical tools
 Types of tools - Description
 Specification of the tools - Models
 Limitations of data and tools
 Types of data
 Resources used and the terrain,
 Theoretical and practical limitations of tools, etc.
 Ethical Issues involved in the study
 In the process of data collection
 In the presentation of results or in the write up

A Research Proposal
A research proposal is like an "action plan" for your
proposed piece of research.
It shows what you believe your research is all about and
what it will cover,
The proposal is expected to;
 Show that you are engaging in genuine enquiry, finding
out about something worthwhile in a particular context,
 Establish a particular theoretical orientation,
 Link your proposed work with the work of others, while
proving you are acquainted with major schools of
thoughts relevant to the topic,
 Establish your methodological approach, and
 Shows your level of understanding and preparedness for
the study,
 Show that the study is understood and is possible.

Structure of a Research Proposal
 Cover Page
 Preliminary Pages
 Acknowledgements
 Abstract
 Table of Content
 List of Acronyms, etc
 Chapter One: Introduction
 Background to Study
 Problem Statement and Justification of Study (Should
contain research questions as the last item)
 Objectives of Study
 Hypotheses
 Significance of Study
 Structure of the Report (Optional)

Structure of a Research Proposal Cont’d
 Chapter Two: Literature Review
 Conceptual Framework
 Theoretical Literature
 Empirical Framework
 Chapter Three: Methodology OR Research Design
 Background to Study Area (Case Study)
 Data Collection
 Sources
 Methods
 Variables on which Data is Collected
 Analytical Tools
 Limitations of Data and Tools
 Ethical Considerations
 Expected Outcomes
 Bibliography OR References List
 Appendices
 Cost of the Study
 Assumptions
 Questionnaire
 Interview Guide, etc

Preparing the Cost of a Study
Getting the costing right for your research proposal
is essential particularly for funded research,
Funding organizations will always consider how
your proposal demonstrates value for money,
In order to estimate the cost of a research, you
need to identify all the needs – in people, materials
(main assets or equipment and working capital),
travel and subsistence, associated activities,
Maintenance & Repairs, Publications,
Memberships, subscriptions and professional
activity, Freight/express deliveries and Postage,
Miscellaneous or Incidental Costs, Telephone, etc).

Elements of Cost of a Study
 Above can be classified under;
 Personnel Related
 Main Researchers
 Research Assistants
 Secretariat staff
 Enumerators
 Drivers
 Specialized staff (computer, geographers, engineers,
etc)/Consultants
 Associated Activities
 Organization of Workshops
 Administration of questionnaire
 Feeding
 Facilities like rentals,
 Insurance expenses
 Membership payments to professional bodies

Elements of Cost of a Study Cont’d
 Equipment/Materials
 Main equipment (vehicles and fueling, computers and accessories,
etc),
 Consumables/Working capital (papers, airtime, internet time, memory
sticks, etc)
 Repairs of equipment/Depreciation of equipment
 Office Furniture,
 Travels (Particularly International)
 Visa Fees
 Return Tickets
 Accommodation and feeding, etc
 Publications and Materials
 Productions of reports, flyers, banners, posters, articles, etc
 Subscription to websites
 Books,
 Translation, etc.
 Miscellaneous or Incidental Costs (Usually a % of total Cost)

Elements of Cost of a Study Cont’d
Parameters that could be considered include;
Number of days
Number of people
Rates of payment of honorarium
Allowances
Duration of travels
Accommodation rates
Suppliers/Direct Market Purchases, etc.

TOPIC 6: DATA COLLECTION
Session Objectives
 To Understand what data is and the various Types of Data,
 To understand the concepts of validity and reliability of data,
 To understand various sources of data,
 To understand secondary data and where to collect it,
 To know various reasons why secondary data should be used,
 To understand the various merits and demerits of using secondary data,
 To understand primary data and where to collect it,
 To know the various reasons why primary data should be used,
 To know the various merits and demerits of using primary data,
 To understand sampling and various types of sampling and when to apply,
 To learn how to generate qustionnaire and how to administer them,
 To learn various types of interviews and how to undertake them,
 To understand Focus Group Discussions and Key Informant Interviews,
 To learn how to collect data through observation,
 To learn about survey research,
 To learn the merits and demerits of using various methods of primary data
collection, etc.

Definition of Data
 Data is a collection of facts, such as numbers, words,
measurements, observations or even just descriptions of
things (usually in raw form).
 Strictly speaking, data is the plural of datum, a single piece
of information. In practice, however, we use data as both
the singular and plural form of the word.
 Data, information, and knowledge are closely related
concepts, but each has its own role in relation to the other.
 Data is collected and analyzed to create information
suitable for making decisions.
 Knowledge is derived from extensive amounts of
experience dealing with information on a subject.
Data Information Knowledge
Processing Extensive usage

Data collection – Meaning
 It is the process of gathering and/or measuring data or
information on variables of interest,
 This should be done in an established systematic
fashion that enables one to answer stated research
questions, test hypotheses, and evaluate outcomes.
 This is a component of research which is common to
all fields of study including physical and social
sciences, humanities, business, etc.
 The methods vary by discipline, but the emphasis on
ensuring accurate and honest collection remains the
same.
 Irrespective of discipline, this must follow a precise
procedure.
 This defines the success or failure of the study

Usefulness of Data
The goal for all data collection is to capture quality
evidence that when analyzed can provide
convincing and credible answers to the research
questions.
Accurate data collection is therefore essential to
maintaining the integrity of research.
Consequences from improperly collected data
include:
 Inability to answer research questions
accurately.
 Inability to repeat and validate the study.
Inaccurate data can arise from
 improper definition of the required data,
 Use of wrong collection methods or wrong
application of collection methods, etc

Types of Data
In business studies, the majority of researchers
need to collect some data to answer their research
questions.
Once the researcher has decided to collect data,
s/he has to decide what kind of data to collect so as
to achieve the research objectives.
The choice of the type of data to collect will depend
on which type of data is needed for a particular
research problem/objective.
Two types of Data exists
Qualitative and Quantitative Data

Quantitative and Qualitative Data
 Quantitative data are measures of values or counts and
are expressed as numbers.
 Quantitative data are data about numeric variables
(e.g. how many; how much; or how often).
Quantitative = Quantity
 Qualitative data are measures of 'types' and may be
represented by a name, symbol, or a number code.
 Qualitative data are data about categorical variables
(e.g. what type).
Qualitative = Quality
 Data collected about a numeric variable will always be
quantitative and data collected about a categorical
variable will always be qualitative. Therefore, you can
identify the type of data, prior to collection, based on
whether the variable is numeric or categorical.

Why are quantitative and qualitative data important?
Quantitative and qualitative data provide different
outcomes, and are often used together to get a full
picture of a population. For example, if data are
collected on annual income (quantitative),
occupation data (qualitative) could also be
gathered to get more detail on the average annual
income for each type of occupation.
Quantitative and qualitative data can be gathered
from the same data unit depending on whether the
variable of interest is numerical or categorical.

Data unit Numeric variable = Quantitative data Categorical variable = Qualitative data
A person "How many children do
you have?"
4 children "In which country were
your children born?"
Cameroon
"How much do you
earn?"
6,000,000 p.a. "What is your
occupation?"
Lecturer
"How many hours do you
work?"
38 hours per week "Do you work full-time
or part-time?"
Full-time
A house "How many square
metres is your house?"
200 square metres "In which city or town is
the house located?"
Buea
A business "How many workers are
currently employed?"
64 employees "What is the industry of
the business?"
Retail
A farm "How many milk cows
are located on the farm?
36 cows "What is the main
activity of the farm?"
Dairy

The difference in emphasis on Qualitative vs Quantitative Data

Discrete and Continuous Data
Quantitative Data can be discrete or continuous
Discrete data is count data and can only take
integral values e.g. the number of students in a
class (you can't have half a student), the number
of children in a family, etc.
Continuous data is measured data and can take
both integral and frictional values or any value
(within a range) e.g. A person's height: could be
any value (within the range of human heights), not
just certain fixed heights, Time in a race: you could
even measure it in fractions of a second, etc.
Scatter plots and line graphs are used to graph
quantitative data whether discrete or continuous.

Nominal and Ordinal Data
Qualitative data could be nominal or ordinal in
nature.
With nominal data; values or observations can
be assigned a code in the form of a number
where the numbers are simply labels. You can
count but not order or measure nominal data.
Examples: Sex, and eye colour.
With ordinal data, values or observations can
be ranked (put in order) or have a rating scale
attached. You can count and order, but not
measure ordinal data. Example: house
numbers, swimming level, ranks in class, etc.

Validity and Reliability of Research Data
 Many reasons why research may not yield good results can
be traced to problems with how data is collected. In
particular, many research mistakes occur due to problems
associated with data validity and data reliability.
 Validity refers to how well data measures what it is
purported to measure. Content validity is important in this
case. (Other types include Face Validity, construct validity,
Criterion-Related Validity, Formative Validity, etc).
 Reliability is the degree to which data produces stable and
consistent results and particularly Internal reliability (Other
types include test-retest reliability, Parallel forms reliability,
etc).
 The source of data and the method used in collecting the
data affect both validity and the reliability of the data and the
eventual usefulness of the research results.

Data Sources
Two main sources exist – Secondary and Primary
Secondary Source: Extracted from Existing Documentations. It is
data which has already been collected by someone else and
has already been processed.
 Secondary data is useful not only to find information to solve our
research problem, but also to better understand and explain our
research problem.
 Having begun with a literature review, data sources are used to
answer the relevant research problem.
 Secondary data sources provide the information that may have
been collected for a different purpose.
 e.g. reports, Catalogues and websites of many companies are
prepared to impress and convince the customer. This may contain
biased information. However, data or information collected by other
organizations such as National Institute of statistics, International
Organizations, etc. offer more neutral information.
Secondary data help researchers in the following ways
 Fine tuning the research problem – stating topic properly,
 Helping in problem formulation
 Answering research questions.
 Deciding about the appropriateness of a certain research method
 Providing benchmarking measures and other findings that can be
compared to each other.

Secondary Data Cont’d
Merits of secondary data
 Saving in time and money-the first and foremost
advantage of using secondary data obviously is the
enormous saving in time and money.
 Can provide high quality and reliable data.
e.g. They are collected and compiled by experts using
rigorous methods. Secondary sources provide
excellent historical data. (Data collected by specialized
institutions and by specialists)
 Facilitates cross-cultural/international research.
e.g. It is easier to compare similar data from two or
more countries or industries, etc.
 Suggests suitable methods to handle data or a
particular research problem.
 Secondary data are not only inexpensive but are
relatively easy to access.
 Begin with secondary data and only when they are
exhausted proceed with primary data.

How to get started when searching secondary Data

Secondary Data Cont’d
Demerits of Secondary Data
 Collected for a different research problem and objective
 e.g. They may not completely fit our problem.
 Need to consider the ‘Fit’ with your research problem and
the validity of the comparison
 e.g. Rather than provide wrong information, it is better to
answer your question partially or not at all.
 Can be expensive (if sourced from commercial
organizations)
 e,g most websites are commercial and may require huge
payments at various intervals,
 Can be inaccurate
 e.g. It is the researcher’s responsibility to check the original
source of data. Wishful thinking rather than facts in their
report.
 Difficulty in cross-cultural comparison.
 e.g. No of TV sets or automobiles per hundreds of the
population, some remittances may be included in GDP.

Types of Secondary Data

Primary Data
This is data collected directly from source or from
the field by the researcher or initiated by the
researcher. It has not been previously published.
It is first hand. Usually collected raw.
Primary data is that which is collected afresh and
for the first time, and thus happen to be original in
character.
When secondary data is not available or is unable
to help answer our research questions, we must
collect data that are relevant to our particular
study directly from source ourselves.
We have several choices as regards the means or
ways of collecting primary data: observations,
experiments, surveys, questionnaires, focus
groups discussions, or interviews as illustrated in
the following figure.

Sources of Primary Data

Merits of Primary Data
 The data is collected for the particular research at
hand. This means that it is more consistent with
research problems and objectives.
 It is usually more reliable and accurate and in the form
required.
 Addresses specific research issues as the researcher
controls the search design to fit the needs.
 Great control; not only does primary data enable the
researcher to focus on specific subjects, it also enables
the researcher to have a higher control over how the
information is collected
 Proprietary Issues - Collector of primary data is the
owner of the information and need not share it with
other companies and competitors.
 It leads to better interpretation since it is based on
relevant issues as they are.
 Recent and up to date showing current trends/issues,
 Collected in the form and in the units required, etc.

Demerits of Primary Data
 Time Consuming - Because of exhaustive nature of the
exercise, the time required to do research accurately is
very long.
 High Cost - Collecting data from source can be very costly.
 More number of resources are required - putting aside
cost and time, other resources like human resources and
materials are needed in larger quantity to conduct surveys
and other primary data collection.
 Dependence on the willingness and ability of respondents.
 It is difficult to get access; to find consumers, companies,
or other target groups who are willing to cooperate and
answer our questions.
 e.g. This is really hard if the case has sensitive issues or
research questions.
 The researher needs to be careful in using proper tools,
procedures and methods of analysis.
 The researher has less degree of control in data collection.
Unexpected factor can influence and interfere with efficient
data collection

Which Source should be Used in a Research?
Factors to be considered;
Nature of study;
Location of the study vis-à-vis the researcher;
Level of Accuracy Required;
Availability of Resources;
Time Required for the Study;
The experience of the Researcher;
Purpose of the Study;
The Methods to be Employed in the Study; etc.

Various Ways of Collecting Primary Data
Observation
This is a data collection tool which entails listening and
watching things or people’s behaviour in a way that allows
some type of learning and analytical interpretation.
 Main advantages: collecting first-hand information, subjective
bias is eliminated if is done accurately, independent of
respondents’ willingness,
 Main disadvantages: observations made by indivuduals -
human error, it is an expensive method, time consuming, can
only provide limited data, .
 Field observation
 Contrived setting
 Participant vs. non-participant
 Mechanical vs. human

Choices for Collecting Primary data through observations

Interviews
Interviews demand real interaction between the
researcher(s) and respondent(s). To run an
interview effectively and efficently without any
disturbances, the researcher(s) need to know
the respondent(s), their background, values and
expectations. The interview process involves;
Preparing for interview – interview guide
Getting an appointment
Pre-interview
The interview
Managing the interview
Post interview

A Typology of Interviews

Personal interviews
Requires a face-to-face contact between interviewer and the interviewee
Major Advantages
 More information and in greater depth can be obtained,
 Possibility of overcoming the resistance on the path of interviewee,
 There is greater flexibility under this method,
 Observation method can as well be applied to recording verbal
answers to various questions,
 The interviewer can usually control which person(s) will answer the
questions,
 The interviewer may catch the informant off-guard and thus may
secure the most spontaneous reactions,
 The language of the interview can be adopted to the ability or
educational level of the person interviewed to avoid misinterpretation,
 The interviewer can collect supplementary information about the
respondent’s personal characteristics and environment which is often
of great value in interpreting results,
• Sample size can be controlled more effectively as there arises no
difficulty of the missing returns; non-response generally remains very
low, etc.

Main Weaknesses
 It is a very expensive method, specially when large and widely
spread geographical sample is taken,
 There remains the possibility of the bias of interviewer as well as that
of the respondent; there also remains the headache of supervision
and control of interviewers,
 Certain types of respondents such as important officials or executives
or people in high income groups may not be easily approachable,
 More-time-consuming, specially when the sample is large and re-
calls upon the respondents are necessary,
 The presence of the interviewer on the spot may over-stimulate the
respondent, sometimes even to the extent that s/he may give
imaginary information,
 The organization required for selecting, training and supervising the
field-staff is more complex with formidable problems,
 Interviewing at times may also introduce systematic errors,
 Effective interview presupposes proper rapport with respondents that
would facilitate free and frank responses. This is often a very difficult
requirement, etc.

Telephone interviews
The chief merits of are:
 It is more flexible in comparison to mailing method.
 It is faster than other methods i.e., a quick way of obtaining
information.
 It may be cheaper than personal interviewing method; here
the cost per response may be relatively low.
 Recall is easy; callbacks are simple and economical.
 There is a higher rate of response than what we have in
mailing method; the non-response is generally very low.
 Replies can be recorded without causing embarrassment to
respondents.
 Interviewer can explain requirements more easily.
 At times, access can be gained to respondents who
otherwise cannot be contacted for one reason or the other.
 No field staff is required.
 Representative and wider distribution of sample is possible.

Demerits include
• Little time is given to respondents for considered answers;
interview period is not likely to exceed five minutes in most
cases.
• Restricted to respondents who have telephone facilities.
• Extensive geographical coverage may get restricted by cost
considerations.
• It is not suitable for intensive surveys where comprehensive
answers are required to various questions.
• Possibility of the bias of the interviewer is relatively high.
• Questions have to be short and to the point; probes are
difficult to handle,
• Difficulties ensuring that the respondents are themselves –
the identity, etc.

Interview by Mail/Email
Merits include;
 Provides great savings in costs; less travelling, transcription
costs, venue renting, etc.
 Wide geographical coverage,
 Needs less equipments like tapes, tape recorders, batteries
and transcribing machines, etc
 Flexibility in terms of when to respond,
 Averagely fast when emails are involved, etc
Demerits include;
 High non response since respondent is usually not obliged,
 Non flexible in terms of the questions,
 Difficulties ensuring that the respondents are themselves –
the identity,
 Accessibility – whether the mails or emails will be received,
 Possibility of misinterpreting questions, etc.

Key Informant Interviews (KIIs)
Purpose: KIIs is to collect information from a wide range of people—including
community leaders, professionals, or residents—who have first hand knowledge
about the community. These community experts, with their particular knowledge
and understanding, can provide insights on the nature of problems and give
recommendations for solutions. This could take any form.
Advantages
 Detailed and rich data can be gathered in a relatively easy and cheap way
 Allows interviewer to establish rapport with the respondent and clarify questions
 Provides an opportunity to build or strengthen relationships with important
community informants and stakeholders
 Can raise awareness, interest, and enthusiasm around an issue
 Can contact informants to clarify issues as needed
Disadvantages
 Selecting the “right” key informants may be difficult so they represent diverse
backgrounds and viewpoints
 May be challenging to reach and schedule interviews with busy and/or hard-to-
reach respondents
 Difficult to generalize results to the larger population unless interviewing many key
informants

Focused Group Discussion (FGD)
 A FGD is a good way to gather together people from similar
backgrounds or experiences to discuss a specific topic of interest.
The group of participants is guided by a moderator (or group
facilitator) who introduces topics for discussion and helps the
group to participate in a lively and natural discussion amongst
themselves.
 The strength of FGD relies on allowing the participants to agree or
disagree with each other so that it provides an insight into how a
group thinks about an issue, about the range of opinion and ideas,
and the inconsistencies and variation that exists in a particular
community in terms of beliefs and their experiences and practices.
 FGDs can be used to explore the meanings of survey findings that
cannot be explained statistically, the range of opinions/views on a
topic of interest and to collect a wide variety of local terms. In
bridging research and policy, FGD can be useful in providing an
insight into different opinions among different parties involved in
the change process, thus enabling the process to be managed
more smoothly. It is also a good method to employ prior to
designing questionnaires

Steps in Conducting Focus groups
Research Methods Lecture by Ntangsi
117

Merits and Demerits of FGDs
Merits
 Provides plurality of ideas - more ideas are generated,
 Quick and relatively easy to go about it,
 The group dynamic can provide useful information that individual
data collection may not provide,
 Useful in gaining insight into a topic that may be more difficult to
obtain through other data collection methods,
Demerits
 Susceptible to facilitator bias,
 The discussion can be dominated or sidetracked by a few
individuals,
 Data analysis may become time consuming and needs to be well
planned in advance,
 Does not provide valid information at the individual level,
 The information is not representative of other groups,
 FGs are a very artificial environment which can influence the
responses that are generated,
 May be very costly, etc.

Collection of Data through Questionnaires
Nature of questionnaire
 Could be structured or non structured
 Open ended or closed
 Instructions very useful
Guidelines for Constructing a Questionnaire
 Simple and concise language
 Realistic demand
 Understanding of the questions
 One dimensional question
 No escape route
 Specific questions not general
 No suggestive questions
 Polite language
 Straightforward questions
 Questions in right order
 Neat and tidy questionnaire
 Do not make assumptions about the respondents,
 Not too long,
 Pre-test, etc.

Categories of structured questions

Scale for Ranking Answers

Questionnaire Administration
As with Interviews, questionnaire can be
administered through face to face, by
telephone, by mail/email or with enumerators
filling in the questions
Face to face or personal contact, by telephone,
by mail/email have the same strengths and
weaknesses like with interviews
Administering questionnaires through
enumerators (Schedules) is useful where the
population is largely illiterate. This increases
response rate and uniformity in responses.
Method very costly and time consuming.

Merits and Demerits of Questionnaire
Merits
 Practical implying the most understood by both
researchers and respondents,
 Large amounts of data can be collected from a large
number of people – wide coverage,
 High possibility of greater validity in the data,
 Uniformity in data collected since same questions are
asked,
 Puts less pressure on the respondents,
 Anonymity can be assured and a high chance of
getting correct responses,
 One of the most flexible tool for data collection
 Useful preliminary tool for more elaborate research,

Merits and Demerits of Questionnaire Cont‘d
Demerits
 Limited Response particularly among very busy people or
illiterates,
 May lack personal Contacts depending on the type used,
 May lead to poor response rate since respondents are not
obliged,
 Possibilities of Incomplete entries,
 Possibilities of manipulated entries,
 Not suitable for delicate, sensitive, intricate and confidential
issues
 May be very costly particularly when a survey is involved,
 May require specialist skills to establish and to extract
useful information from filled questionnaire,
 May be time consuming, etc.

Sampling
 All items in any field of inquiry constitute a ‘Universe’ or ‘Population.’
A complete enumeration of all items in the ‘population’ is known as a
census. (Requires lots of time, money, energy and expertise).
 Sampling refers to selecting only a few items or respondents
(Sample) from the population to be representative of the total
population.
 A sample (n) < the population (N).
 A sample design/type is a plan or an instrument for obtaining a
sample from a given population. It refers to the technique or the
procedure that the researcher intends to adopt in selecting items
from the universe or population to constitute the sample.
 There are many sample designs from which a researcher can
choose. Some designs are relatively more precise and easier to
apply than others. Researchers must select or prefer sample designs
which should be reliable and appropriate for any given research.
 Obviously, researcher must select that design which, for a given
sample size and for a given cost, has a smaller sampling error
 A good sample should be that which is representative of the
population from which it is drawn.

Why Do Sampling?
 In reality there is simply not enough resources: time,
energy, money, labour, expertise, equipment, access
to suitable sites to measure every single item of the
population. Only governments can undertake
census.
 In some Cases, samples may be more accurate than
census such that even in a census, sampling is done
to ascertain the census results
 To be able to undertake studies with the use of
primary data,
 To be able to do cross – checking of study results in
a relatively shorter time and few resources,
 Therefore an appropriate sampling strategy is
adopted to obtain a representative, and statistically
valid sample of the whole

The Sampling Process

What to Consider in Choosing a Sampling Design
Type of universe – whether finite or infinite (but
necessary to define it to be finite).
The nature of the universe in terms of
homogenous / heterogenous population.
Sampling unit - a geographical one such as state,
district, village, etc., or a construction unit such as
house, flat, etc., or it may be a social unit such as
family, club, school, etc., or it may be an individual.
Comprehensive Source list also known as
‘sampling frame’ from which sample is to be drawn.

What to Consider - Cont‘d
 Size of sample i.e. the number of items to be selected
from the universe to constitute a sample.
 Larger sample sizes are more accurate
representations of the whole,
 The sample size chosen is a balance between
obtaining a statistically valid representation, and the
time, energy, money, labour, equipment and access
available
 Budgetary constraint because the size of the sample
and also the type of sampling have cost implications.
 Knowledgeability in applying the chosen sampling
type,
 Sampling error, etc.

Characteristics of a Good Sampling Design
Sample design must result in a truly representative
sample.
Sample design must be such which results in a
small sampling error.
Sample design must be viable in the context of
funds available for the research study.
Sample design must be such that systematic bias
can be controlled in a better way.
Sample design should be such that the results of
the sample study can be applied, in general, for
the universe with a reasonable level of confidence.

Types of Sampling Designs
1. Probability Sampling
Simple random sampling
Systematic random sampling
Stratified random sampling
Multistage sampling
Multiphase sampling
Cluster sampling
2. Non-Probability Sampling
Convenience sampling
Purposive sampling
Quota sampling, etc.

Random Sampling
 Applicable when population is small, homogeneous & readily available
 All subsets of the frame are given an equal probability. Each element of the
frame thus has an equal probability of selection.
 It provides for greatest number of possible samples. This is done by
assigning a number to each unit in the sampling frame.
 A table of random number or lottery system is used to determine which units
are to be selected.
Merits
 Estimates are easy to calculate.
 Simple random sampling is always an Equal Prob. Selection (EPS) design,
and thus could give little sample error.
Disadvantages
 If sampling frame is large, this method becomes impracticable.
 Minority subgroups of interest in population may not be present in sample in
sufficient numbers for study.
 In heterogeneous situations, sample error becomes very large.
 The cost of obtainning the sample can be high if the units are widely
scattered.
Research Methods Lecture by Ntangsi
132

Systematic Sampling
 This relies on arranging the target population according to some ordering
scheme and then selecting elements at regular intervals through that ordered
list.
 Systematic sampling involves a random start and then proceeds with the
selection of every kth element from then onwards. In this case, k=(population
size/sample size).
 It is important that the starting point is not automatically the first in the list, but
is instead randomly chosen from within the first to the kth element in the list.
 A simple example would be to select every 10th name from the telephone
directory (an 'every 10th' sample, also referred to as 'sampling with a skip of
10').
 Usually used in Production Lines for quality control purposes.
Merits
 Sample easy to select
 Suitable sampling frame can be identified easily
 Sample evenly spread over entire reference population
Demerits
 Sample may be biased if hidden periodicity in population coincides with that
of selection.
 Difficult to assess precision of estimates from one survey.

Stratified Sampling
 Where population embraces a number of distinct categories, the frame can be
organized into separate "strata." Each stratum is then sampled as an
independent sub-population, out of which individual elements can be randomly
selected. Converting heterogeneous groups into homogeneous sub groups.
 Every unit in a stratum has same chance of being selected.
 Using same sampling fraction for all strata ensures proportionate representation
in the sample.
 Adequate representation of minority subgroups of interest can be ensured by
stratification & varying sampling fraction between strata as required.
 Since each stratum is treated as an independent population, different sampling
approaches can be applied to different strata.
Merits
 A stratified random sampling can give higher precision with the same sample size
or alternatively the same precision with a smaller sample. A stratified random
sampling can also give separate results for each stratum.
 Converts heterogeneous groups into homogeneous sub groups.
Drawbacks
 First, sampling frame of entire population has to be prepared separately for each
stratum
 Second, when examining multiple criteria, stratifying variables may be related to
some, but not to others, further complicating the design, and potentially reducing
the utility of the strata.
 Finally, in some cases (such as designs with a large number of strata, or those
with a specified minimum sample size per group), stratified sampling can
potentially require a larger sample than would other methods

Cluster Sampling
 This is an example of 'two-stage sampling' .
 First stage a sample of areas is chosen;
 Second stage a sample of respondents within those areas is
selected.
 Population divided into clusters of homogeneous units, usually
based on geographical contiguity.
 Sampling units are groups rather than individuals.
 A sample of such clusters is then selected.
 All units from the selected clusters are studied or a few could be
studied for some groups.
Advantages
 Cuts down on the cost of preparing a sampling frame.
 This can reduce travel and other administrative costs.
Disadvantages
 Sampling error is higher for a simple random sample of same size.
 If there is large variation between clusters in the variables to be
examined, the method may yield poor precision.

Multistage Sampling
 Complex form of cluster sampling in which two or more levels of
units are embedded one in the other.
 First stage, random number of divisions chosen in all regions.
 Followed by random number of districts, villages.
 Then third stage units will be houses.
 All ultimate units (houses, for instance) selected at last step are
surveyed.
 This technique, is essentially the process of taking random samples
of preceding random samples.
 Not as effective as true random sampling, but probably solves more
of the problems inherent to random sampling.
 An effective strategy because it banks on multiple randomizations.
As such, extremely useful.
 Multistage sampling used frequently when a complete list of all
members of the population do not exist or is inappropriate.
 Moreover, by avoiding the use of all sample units in all selected
clusters, multistage sampling avoids the large, and perhaps
unnecessary, costs associated with traditional cluster sampling.

Multi phase Sampling
Sampling is done in phases such that at each
phase, a particular objective is achieved.
Usually starts with a broader objective at initial
phase and then other specific issues are
addressed through other phases.
Survey by such procedure is less costly, less
laborious & more purposeful
May require more resources as the process
goes on. Mostly used in medical research
where there is initial screening and the sample
selected is tested for more precise diseases.

Non-Probability Sampling
Quota Sampling
 The population is first segmented into mutually
exclusive sub-groups, just as in stratified sampling.
 Then judgment used to select subjects or units from
each segment based on a specified proportion.
 For example, an interviewer may be told to sample 200
females and 300 males between the age of 45 and 60.
 It is this second step which makes the technique one of
non-probability sampling.
 In quota sampling the selection of the sample is non-
random .
 For example interviewers might be tempted to interview
those who look most helpful. The problem is that these
samples may be biased because not everyone gets a
chance of selection. This random element is its greatest
weakness and quota versus probability has been a
matter of controversy for many years

Convenience Sampling
 Sometimes known as grab or opportunity sampling or accidental or
haphazard sampling.
 A type of non probability sampling which involves the sample being drawn
from that part of the population which is close to hand. That is, readily
available and convenient.
 The researcher using such a sample cannot scientifically make
generalizations about the total population from this sample because it
would not be representative enough.
 For example, if the interviewer was to conduct a survey at a shopping
center early in the morning on a given day, the people that he/she could
interview would be limited to those there at that given time, which would not
represent the views of other members of society in such an area, if the
survey was to be conducted at different times of the day and several times
per week.
 This type of sampling is most useful for pilot testing.
 In social science research, snowball sampling is a similar technique, where
existing study subjects are used to recruit more subjects into the sample.

Judgmental sampling or Purposive sampling
The researcher chooses the sample based on
who s/he thinks would be appropriate for the
study. This is used primarily when there is a
limited number of people that have expertise in
the area being researched. Similar to KII.
Usually gives high response rate.
Also gives a high sample error or bias.
Reduces non response rate.

Panel Sampling
 Method of first selecting a group of participants through
a random sampling method and then asking that group
for the same information again several times over a
period of time.
 Therefore, each participant is given same survey or
interview at two or more time points; each period of data
collection is called a "wave".
 This sampling methodology often chosen for large scale
or nation-wide studies in order to gauge changes in the
population with regard to any number of variables from
chronic illness to job stress to weekly food expenditures.
 Panel sampling can also be used to inform researchers
about within-person health changes due to age or help
explain changes in continuous dependent variables such
as spousal interaction.
 There have been several proposed methods of
analyzing panel sample data, including growth curves.

Which Sampling Method is Preferable?
 Factors to be considered: These are same as choosing a
source of data and/or method of data collection.
 Nature of study;
 Nature of Population;
 Level of Accuracy Required;
 Availability of Resources;
 Time Required for the Study;
 The experience of the Researcher;
 Purpose of the Study;
 Scale of study,
 The expertise of the person(s) involved,
 Level of Freedom involved,
 The Methods to be Employed in the Study; etc.

Which Sampling Method is Preferable Cont’d?
 Examples
 Determining the proportion of undernourished five year olds in a
village.
 Investigating nutritional status of preschool children in the SWR.
 Assessing the Performance of Micro financial Institutions in Douala.
 Assessing the Factors that motivate workers in CDC.
 Examining the rate of adoption of ICTs in Higher Institutions of
learning in Cameroon.
 Assessing the Impact of Corrupt Practices on Students’ Performance
in UB.
 Assessing the Impact of CSR of SONARA on the Limbe Municipality.
 Assessing the role played by the community in the development of
the CSR of MTN Cameroon.
 Estimating the costs of domestic violence on men in Fako Division.
 Assessing the Role of Advertisement on the consumption pattern of
Guinness Products in Douala.

7. DATA PROCESSING AND ANALYSIS
The data, after collection, has to be processed and
analyzed for it to be useful.
 Technically speaking, processing implies editing, coding,
classification and tabulation of collected data so that
they are amenable to analysis.
 The term analysis of data refers to the break down of
data OR the computation of certain measures along with
searching for patterns of relationship that exist among
data-groups.
 Data analysis provides results that need to be
interpreted and discussed so as to achieve the
objectives of a study.
 In the process of data analysis, relationships or
differences supporting or conflicting with original or new
hypotheses should be subjected to statistical tests to
validate various hypotheses.

Data Processing Operations
1. Editing
 This is a process of examining the collected raw data
(specially in surveys) to detect errors and omissions and to
correct these when possible.
 Editing involves a careful scrutiny of the completed
questionnaires and/or schedules to eliminate inconsistent
and contradictory responses.
 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.
 Two types of editing exist; field editing and central editing.
 Field editing consists in the review of the reporting forms by
the enumerator to be more legible and to avoid
abbreviations or short hand. This do not involve changing
nature of responses but rather tries to clean various
unorthodox styles of writing for clarity purposes.

Editing Cont’d
 Central editing should take place when all forms or
schedules have been completed and returned to the
office. This type of editing implies that all forms should
get a thorough editing by a single editor in a small study
and by a team of editors in case of a large inquiry.
 Editor(s) may correct the obvious errors such as an
entry in the wrong place, entry recorded in months when
it should have been recorded in weeks, and the like.
 In case of inappropriate or missing replies, the editor can
sometimes determine the proper answer by reviewing
the other information in the questionnaire.
 At times, the respondent can be contacted for
clarification if possible.
 The main objective of central editing is to harmonise the
responses

2. Coding
 This 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 and should be exhaustive
and mutually exclusive.
 Another rule to be observed in coding is that of
unidimensionality, implying single meaning.
 Coding is necessary for efficient analysis and through it
the several replies from the field may be reduced to a
small number of classes which contain the critical
information required for analysis.
 Coding decisions should usually be taken at the
designing stage of the questionnaire.

3. Classification
Classification of data means the process of
arranging data in groups or classes on the
basis of common characteristics.
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.
Classification necessitates Data having a
common characteristics to be placed in one
class and in this way the entire data get divided
into a number of groups or classes.

Data Classification Cont’d
 Classification can take one of the following two types, depending
upon the nature of the phenomenon involved:
 Classification according to attributes - this involves describing the
data (such as literacy, gender, honesty, etc.) – Qualitative Data
 Descriptive characteristics refer to qualitative phenomenon which
cannot be measured quantitatively; only their presence or absence in
an individual item can be noticed.
 Such classification can be simple classification or manifold
classification.
 In simple classification we consider only one attribute and divide the
universe into two classes —one class consisting of items possessing
the given attribute and the other class consisting of items which do
not possess the given attribute – Dummy Variables
 In manifold classification we consider two or more attributes
simultaneously, and divide that data into a number of classes (total
number of classes of final order is given by 2n; where n = number of
attributes considered).
 Whenever data are classified according to attributes, the researcher
must see that the attributes are defined in such a manner that there is
least possibility of any doubt/ambiguity concerning the said attributes.

Data Classification Cont’d
Classification according to class intervals - this
involves numerical characteristics (such as weight,
height, income, etc.) – Quantitative Data
 Various classes will depend on the volume of data
and on the intervals. The interval could be equal or
unequal. If equal, Sturges rule can be used in
determining the class interval.
i = R/(1 + 3.3 log N).
where i = size of class interval;
R = Range (i.e., difference between the
values of the largest item and smallest item among
the given items);
N = Number of items to be grouped.

4. Tabulation
 The results of various classification are tables.
Tabulation is essential because of the following
reasons.
It conserves space and reduces explanatory and
descriptive statement to a minimum.
It facilitates the process of comparison.
It facilitates the summation of items and the
detection of errors and omissions.
It provides a basis for various statistical
computations to obtain results.
These results need to be interpreted and
discussed to show what have been found out in
the research process.

Generally accepted principles of tabulation:
 Every table should be named and should have a clear, concise and
adequate title
 The units of measurement under each heading or sub-heading must
always be indicated
 Source or sources from where the data in the table have been
obtained must be indicated just below the table.
 Abbreviations should be avoided to the extent possible and ditto
marks should not be used in the table.
 Table should be made as logical, clear, accurate and simple as
possible. If the data happen to be very large, they should not be
crowded in a single table for that would make the table unwieldy and
inconvenient.
 Miscellaneous and exceptional items, if any, should be usually placed
in the last row of the table.
 Explanatory footnotes, if any, concerning the table should be placed
directly beneath the table, along with the reference symbols used in
the table.

Common Problems in Data Processing
Two main problems could exist;
The problem concerning “Don’t know” (or DK)
responses. When these are few, no problem but
these are many, questionnaire may need to be
reviewed and process repeated.
Use or percentages. This must be done
properly

8. ELEMENTS/TYPES OF ANALYSIS
This implies the computation of certain indices or
measures along with searching for patterns of
relationship that exist among the data groups.
Analysis, particularly in case of survey or
experimental data, involves estimating the values
of unknown parameters of the population and
testing of hypotheses for drawing inferences.
Analysis may, therefore, be categorized as
descriptive analysis or/and inferential analysis
Discussed by Dobdinga

9. INTERPRETATION AND REPORT WRITING
After collecting and analyzing the data, the researcher
has to accomplish the task of drawing inferences
followed by report writing.
This has to be done very carefully, otherwise misleading
conclusions may be drawn and the whole purpose of
doing the research may be defeated.
It is only through proper interpretation and discussions
that the researcher can expose relations and processes
that underlie his findings.
In case of hypotheses testing studies, if hypotheses are
tested and upheld several times, the researcher may
arrive at generalizations. But in case the researcher had
no hypothesis to start with, s/he would try to explain
his/her findings on the basis of the specific objectives.

Objectives of Session
 Understand the meaning of interpretation and discussion of
research findings,
 Understand why and how to go about interpretation and
discussion of results,
 Master the various techniques of interpretation and
 Understand the differences between interpretation and
 Master the art of writing research reports,
 How to go about reviewing a report,
 The content of a research report,
 The language to be used in a research report,
 The various ways of editing and proof reading to get a final
report,
 Various precautions to take at each stage of report writing,
 Various types of reports.

Meaning of Interpretation and Discussion of Results
Interpretation
 Interpretation refers to the task of attaching meaning to the results
from data analysis.
 Interpretation also imply the establishment of some explanatory
concepts. In one sense, interpretation is concerned with
relationships within the results of the study.
Discussion
 Discussion refers to drawing inferences from the results. In fact, it
is a search for broader meaning of the research results in the
context of how useful are the results in policy issues.
 Discussion also imply the effort to establish continuity in research
through linking the results of a given study with those of another,
 Discussion thus extends beyond the results of the study to include
the results of other researches, theories and hypotheses.

Meaning Cont’d
Interpretation and discussion thus constitute the
ways through which the factors that seem to
explain what has been observed by the researcher
in the course of the study can be better understood
and these also provide a theoretical conception
which can serve as a guide for further researches.
This section is often considered the most important
part of a research because this is where you:
 demonstrates your ability as a researcher to think
critically about an issue,
 develop creative solutions to problems based upon
a logical synthesis of the findings,
 formulate a deeper, more profound understanding
of the research problem under investigation.

Business Research Methodology Lectures

Business Research Methodology Lectures

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (20)

Ähnlich wie Business Research Methodology Lectures

Ähnlich wie Business Research Methodology Lectures (20)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

Business Research Methodology Lectures