Elements of research methods

1 of 46
ELEMENTS OF RESEARCH METHODS
HK NDAMBIRI

2 of 46
PART ONE
Definition and meaning of research
Research is a process of arriving at effective solutions to problems through systematic collection,
analysis and interpretation of data. It implies exhaustive study, investigation or experimentation
following some logical sequence. It involves a critical analysis of existing conclusions or theories
with regard to newly discovered facts. Research, therefore, means a continued search for new
knowledge and understanding of the world around us.
Basic features of Research
A good research should have the following features.
o It demands a clear statement of the problem and therefore the purpose should be clearly
defined
o It requires a planned research process (it is not aimlessly “ looking” for something in the
hope that the researcher will come across a solution)
o It builds on existing data, using both positive and negative findings
o New data should be collected as required and be organized in such a way that they
answer the research question(s)
o It is a scientific and systematic process
o There is adequate analysis for decision making
o High ethical standards are applied
o Conclusions are justified
o It should be reproducible → results and conclusions of the study should be supported by
the same methodology when used in a different study with similar conditions.
o It should be objective → conclusions should be based on observed phenomena and not
influenced by personal prejudice or emotions.
o It should have validity → concerned with whether conclusions from the sample are
applicable to larger groups.
o It should be possible to have generalizations → whether findings or conclusions from the
sample setting / group are directly applicable to larger populations in different settings.
Purpose / significance of Research
1) The main purpose of research is to discover new knowledge. This involves the discovery of
new facts, their correct interpretation and practical application.

3 of 46
2) To describe a phenomenon. Accurate identification of any event involves thorough
description. Description then provides knowledge.
3) To enable prediction. This is the ability to estimate phenomenon A given phenomenon B. A
set of variables could be used to predict a given variable.
4) To enable control. Control is concerned with the ability to regulate the phenomenon under
study. Usually, one phenomenon is manipulated in order to exert control over another, for
example, when conducting an experiment in a laboratory.
5) To enable explanation of the phenomena. Explanation involves accurate observation and
measurement of a given phenomena. In order to explain phenomena, one should be able
to describe it, predict its occurrence and observe factors that cause its occurrence with
accuracy and certainty.
6) To enable theory development. This involves formulating concepts, laws and
generalizations about a given phenomenon. Research is also conducted in an attempt to
confirm or validate existing theories.
Glossary of Some Basic Terms in Research
o Population → refers to an entire group of individuals, events or objects having a common
observable characteristic. It is the aggregate of all that conforms to a given specification.
o Sample → it is a smaller group obtained from the accessible population. Each member or
case in the sample is referred to as a subject or respondent or interviewee.
o Sampling → it is the process of selecting a sample for a study in such a way that the
sample selected represents the population from which the sample was selected. The
purpose of sampling is to secure a representative group which will enable the researcher
to gain information about the population. Various methods are used to do sampling.
o Variable → this is a measurable characteristic that assumes different values among the
subjects. It is therefore a logical way of expressing a particular attribute in a subject.
Some variables are expressed quantitatively while others are expressed qualitatively in
categories. There are different classifications of variables with the main ones being
independent, dependent and extraneous variables. An independent variable (also known
as predictor variable) is a variable that a researcher manipulates to determine its effect
or influence on another variable. It predicts the amount of variation that occurs in another
variable. A dependent variable (also known as the criterion variable) is a variable that
attempts to indicate the total influence arising from the effects of independent variable(s).

4 of 46
A dependent variable therefore varies as a function of the independent variable.
Extraneous variables are those variables that affect the outcome of a research study
either because the researcher is not aware of their existence or, if the researcher is
aware, he does not control for them. Therefore, extraneous variables will influence the
results of a study unless they are controlled for through an appropriate procedure.
Extraneous variables include intervening variables, antecedent variables, suppressor
variables and distorter variables.
o Conceptual or Theoretical Definition of Variables → this is the way of specifying
precisely what the researcher means when he uses a particular term to refer to a variable.
o Operational Definition of Variables → this refers to the measurement of a variable. It is
the description of the operation that will be used in measuring the variable. Operational
definition may be stated quantitatively or categorically. For example, operational
definition of the variable “age” can be stated as the number of years or the date of birth.
The operation definition for the variable “type of instruction” may be stated categorically
as lecture, group discussion, individual tutoring, independent study and so on.
o Data → refers to all the information a researcher gathers for his / her study. There are
two types of data: primary and secondary data. Primary data refers to the information a
researcher obtains from the field, that is, from the subjects in the sample. Secondary data
is the information a researcher obtains from research articles, books, magazines, journals
etc. Data may also be quantitative (numerical) or qualitative (words, phrases).
o Parameter → it is a characteristic that is measurable and can assume different values in
the population. The difference between a variable and a parameter is that a parameter
refers to a population characteristic while a variable is related to a characteristic of a
sample drawn from the population.
o Statistics → these are indices which are derived from data through statistical procedures.
They include means, standard deviation, correlation coefficient, etc.
o Descriptive Statistics → these are indices that describe a given sample. They include
measures of central tendency (mean, mode, median) measures of dispersion (range,
standard deviation, variance) distributions (percentages, frequencies) and relationships
(correlation).

5 of 46
o Inferential Statistics → this is a branch of statistics which researchers use to draw
inferences / conclusions about a given phenomenon in the population. Such inferences are
based on the results.
o Objectives → an objective is any kind of desired end or condition. In research, objectives
are specific aspects of the phenomenon under study that the researcher desires to bring
out at the end of the research study.
o Literature Review → it involves locating, reading and evaluating reports of previous
studies, observations and opinions related to the planned study. It therefore leads to
appreciating and understanding the research that has already been done in one’s area of
interest.
o Problem Statement → it is a specific statement that clearly conveys the purpose of the
research study. It focuses on the phenomenon that the researcher desires to describe,
predict, control or explain.
o Unit of Analysis → it is also called the unit of statistical analysis. It refers to those units
that are initially described for the purpose of aggregating their characteristics in order to
describe some larger group or abstract phenomenon. They are the individual units about
which or whom descriptive or explanatory statements are to be made. Examples include
human beings, cities or geographical regions. For example, in studies dealing with
composite units such as schools, families, industries, etc., the information or data required is
obtained from an individual person but the results obtained from the analysis of such
information relate to the composite unit which is the unit of analysis.
o Units of Observation → a unit of observation is the subject, object, item or entity from
which the data required for the study is obtained. It can be an individual person, a house,
an animal, etc. In most studies, the unit of observation is also the unit of analysis. For
example, if a researcher wants to asses the effectiveness of a new drug in lowering the
blood pressure of hypertension patients, each of the patients in the sample is a unit of
observation because the required data is obtained from the patient. Each patient is also a
unit of analysis.
o Hypothesis → this is a researcher’s anticipated explanation or opinion regarding the
result of the study.

6 of 46
o Theory → this is a set of concepts or constructs and the interrelations that are assumed to
exist among those concepts. A theory provides a basis for establishing the hypothesis to
be tested in the study.
Types of Research
Research can be classified in different ways based on the following:
o Method of analysis
o Purpose
o Method of data collection
These broad classifications are not necessarily mutually exclusive and a researcher can use more
than one. From these classifications, the following four broad types of research can be identified.
1) Exploratory research
It is undertaken when few or no previous studies exist. The aim is to look for patterns,
hypotheses or ideas that can be tested and will form the basis for further research. Typical
research techniques would include case studies, observation and reviews of previous related
studies and data.
2) Descriptive research
It can be used to identify and classify the elements or characteristics of the subject.
Quantitative techniques are most often used to collect, analyze and summarize data. It
includes surveys and fact finding enquiries of different kinds. Its major purpose is to describe
the state of affairs as it exists at present. The term ex-post facto is often used for descriptive
research studies in social science and business research. The researcher has no control over the
variables. He can only report what has happened or what is happening.
3) Analytical research
It often extends the descriptive approach to suggest or explain why or how something is
happening e.g. underlying causes of industrial action. An important feature of this type of
research is in locating and identifying the different factors (or variables) involved. The
researcher has to use facts or information already available and analyze these to make a
critical evaluation of the material.
4) Predictive research

7 of 46
Its aim is to speculate intelligently on future possibilities based on close analysis of available
evidence of cause and effect e.g. predicting when and where future industrial action might
take place.
Within these four broad types of research, other types of research can be identified depending
on the approaches used to carry out the research. These further types are as follows.
a) Qualitative and Quantitative research
Qualitative research involves examining and reflecting on the less tangible aspects of a
research subject e.g. values, attitudes, perceptions, attributes etc. It includes designs,
techniques and measures that do not produce discrete numerical data. More often the
data are in the form of words rather than numbers and these words are often grouped
into categories. Though this type of research can be easier to start, it can be often difficult
to interpret and present the findings. The findings can also be challenged more easily.
There are three methods used to collect qualitative data. These are:
o Direct observation → where the required behaviour is observed in a particular
setting.
o Participant observation → where data are collected by an observer who is a
regular, full time participant in the activities being observed. The researcher
compiles data through long term interaction with the subjects in the context of their
everyday lives.
o Interview method → this is face-to-face interaction between the researcher and
the subjects. The researcher uses an interview schedule.
Quantitative research emphasizes on collecting and analyzing numerical data. It
concentrates on measuring the scale, range, frequency etc of phenomena. It includes
designs, techniques and measures that produce discrete numerical or quantifiable data.
This type of research, although harder to design initially, is usually highly detailed and
structured and results can be easily collated and presented statistically.
b) Basic and Applied research
Basic research is also called Pure or Fundamental research. The primary aim of basic
research is to improve knowledge generally, without any particular applied purpose in
mind at the outset. A basic researcher is normally motivated by intellectual curiosity and
need to come up with a particular solution. Another focus of basic research is to generate
new knowledge in order to refine and expand existing theories. Basic research is usually,

8 of 46
but not always, conducted in controlled laboratory situations. In basic research, there is no
consideration of the practical application of the findings to actual problems or situations.
Applied research is conducted for the purpose of applying or testing theory and
evaluating its usefulness in solving problems. It is designed from the start to apply its
findings to a particular situation.
c) Action and Evaluation research
Action research is conducted with the primary intention of solving a specific, immediate
and concrete problem in a local setting e.g. investigating ways of overcoming water
shortage in a given area.
Evaluation research is a systematic process of collecting and analyzing data in order to
make decisions. It is thus a process of determining whether the intended results were
realized.
d) Causal-comparative research
This is used to explore relationships between variables. The main purpose is therefore to
determine reasons or causes for the current status of the phenomenon under study. In this
research the variable can not be manipulated as is the case with experimental research.
This research is at times called ex-post facto research because causes are studied after
they have exerted their effects on another variable.
e) Survey and Historical research
A survey is an attempt to collect data from members of a population in order to determine
the current status of that population with respect to one or more variables. Survey
research is thus a self-report study which requires the collection of quantifiable information
from the sample. It could be descriptive, exploratory or involving advanced statistical
analysis e.g. a market research used to evaluate the acceptance and use of a product.
Historical research is the study of a problem that requires collecting information from the
past. It involves studying, understanding and experiencing past events. Historical research
studies do not gather data by administering instruments to individuals. It seeks data that is
already available. It consists of locating, integrating and evaluating evidence from
physical relics (objects), written records or documents in order to establish facts or
generalizations regarding past or present events, human characteristics or other problems
in question.

9 of 46
f) Case studies
A case study is an in-depth investigation of an individual, group, institution or phenomenon.
The case under study is reviewed as an example of a class of events or a group of
individuals. The investigation therefore makes a detailed examination of a single subject,
group or phenomenon.
g) Deductive and Inductive research
Deductive research moves from general ideas / theories to specific particular situations.
The particular is deduced from the general situation e.g. a study on professionalism in
broad terms moving to what professionalism is to a particular person in a given field or
industry.
Inductive research moves from specific particular situations to make or infer broad general
ideas / theories.
h) Conceptual and Empirical research
Conceptual research is related to some abstract idea(s) or theory. It is generally used by
philosophers and thinkers to develop new concepts or 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 experiment. It can also be called experimental
type of research. The researcher must first provide himself with a working hypothesis and
then work to get enough facts (data) to prove or disapprove his hypothesis.
NB: The above description of the types of research brings to light the fact that there are two
basic approaches to research. These are:
i) Qualitative approach
ii) Quantitative approach
The Research Process
A research passes through several stages before completion, starting from planning and ending
with writing the final report. These stages can be summarized under two broad headings:
o Planning the research
o Executing the research

10 of 46
Planning the research involves the following.
o Purpose of the study or statement of the problem.
o Scope of the study → that is, it’s coverage with regard to the type of information, the
subject matter and geographical area. Therefore, one must also consider the object of
enquiry, availability of time and resources.
o Unit of data collection → units must be clearly defined for the purpose of investigation.
o Technique of data collection.
o Choice of frame; frame refers to the listing of all units in the population under study.
o Degree of accuracy required.
o Miscellaneous considerations → considerations should be given to various other matters
such as whether the enquiry is official or not, confidential or not, direct or indirect, etc.
Executing the research involves the following.
o Setting up an administrative organization. This depends on the scope; for instance, if the
investigation covers a large area, regional offices may be set up to supervise the survey.
o Design of forms → such as designing questionnaires.
o Selection, training and supervision of field investigators.
o Control over the quality of the field work and field edit → this includes checking of such
items such as filled questionnaires to check out for any omissions, inconsistencies, etc.
o Follow up of non-response.
o Processing of data.
o Preparation of report.
In summary, a research progresses in the following steps.
1) Identification and statement of the problem and objectives → the problem must be clearly
identified and stated and the objectives of survey clearly outlined to enable collection of
relevant data.
2) Choice of collection procedure → the researcher has to determine how data is to be
collected; for instance, whether through census, sampling or whatever other appropriate
method. Alongside that, the researcher has to determine the appropriate tools for data
collection, such as questionnaires, interviews, etc, depending on scope and nature of
investigation.
3) Construction of questionnaires → this is done in such a way as to ensure that all the
relevant data is captured.

11 of 46
4) Pilot survey → before the actual investigation is undertaken, the investigator must conduct
a survey. This is performed on a small group that has similar characteristics to that of the
population or sample under study. In this way, any amendments that may arise are made
before the actual survey.
5) Collection of data from the respondents.
6) Editing → correcting any mistakes that may have been made during data collection.
7) Compilation and summary → data collected is compiled and summarized through manual
handling or by means of electrical and electronic devices. This can be done in tables and
graphs.
8) Data analysis → once summarized, the information is analyzed by means of suitable tools
of analysis as informed by the objectives of the study. Useful conclusions are then drawn
from the analysis and statements made.
9) Report writing → this consists of an essay covering the original objective(s) of the
investigation, the significance of data in relation to the objective(s) and the major findings
and conclusions drawn from the analysis of the data.

12 of 46
PART TWO
THE RESEARCH PROCESS
The research process starts by formulating a research problem that can be investigated through
research procedures.
Research Problem
This refers to some difficulty which a researcher experiences in the context of either a theoretical
or practical situation and wants to obtain a solution for the same.
Components of a Research Problem
1) There must be an individual or group which has some difficulty or the problem.
2) There must be some objective(s) to be attained.
3) There must be alternative means (or other courses of action) for obtaining the objectives(s)
one wishes to attain. Thus, there must be at least two means available to a researcher.
4) There must remain some doubt in the mind of a researcher with regard to the selection of
alternatives. This means that the research must answer the question concerning the relative
efficiency of the possible alternatives.
5) There must be some environment to which the difficulty pertains.
Identifying a Research Problem
The first step in selecting a research problem is to identify the broad area of interest. Such an
area should be related to the professional interests and goals of the researcher. The next step is
to identify a specific problem within the broad area that will form the basis of the research study.
Hence the researcher should narrow down from the broad area to the specific problem. In doing
this, the researcher should consider the key factors that help in indentifying a researchable
problem.
Points to Consider in Selecting the Research Problem
1) The problem should be an important one. As such, it should:
o Lead to findings that have widespread implications in a particular area.
o Challenge some commonly held truism.
o Review the inadequacies of existing laws, views or policies
o Cover a reasonable scope. The scope depends on the time available, resources
and availability of subjects or units of study.

13 of 46
2) Subject that has been overdone should not be chosen because it could be difficult to throw
a new light in such a case.
3) Controversial subjects should be avoided.
4) The subject selected should be familiar and feasible so that the related research material
or sources of research are within ones reach.
5) The selection should be preceded by a preliminary study especially when the field of
inquiry is relatively new and does not have available a set of well developed techniques.
Ways of Identifying a Specific Research Problem from the Broad Area
a) Existing theories → a theory contains generalization and hypothesized principles which
can be scientifically tested.
b) Existing literature → other written articles on the broad area give the researcher a good
background of basic information and an insight into various issues that could be studied.
c) Discussions with experts → these involve experienced and well informed researchers in the
particular area that one may be interested in.
d) Previous research studies → a review of such studies provides a researcher with
researchable projects that would, when carried out, add to the knowledge that has been
built up by other researchers.
e) Replication → involves carrying out a research project that has been done previously. In
this case the problem and procedures of the research are identical to a study that was
previously done. The aim is to find out whether findings hold over time and across regions.
f) The media → issues frequently reported can also form the basis of a research problem.
Such issues are discussed in public fora and hence they are important to the majority of
the people.
g) Personal experience → these lead to vivid images or an intuition, thereby helping the
researcher to formulate a specific research problem from a general area.
Summary
After identifying the problem, the researcher should be able to write the title of the research
study and the introduction section. The title should be short and simple, yet informative. The titles
enable the reader to get some initial information about the area of research covered and it is
therefore a pointer to the content of the study. The title should also give an indication of the major
variables of the research (both the independent and dependent variables), the target population

14 of 46
and the geographical location of the research. The title is also used for indexing once the
document is official. The introduction section consists of the background of the study, the problem
statement, the objectives, hypotheses / research questions, significance / justification of the
research and the study area. The background information should broadly introduce the topic
under investigation. A global, regional and national overview of the research topic is briefly
discussed e.g. if the research is about domestic tourism in Kenya, the research should give an
overview of the status of domestic tourism globally, regionally (in Africa or East Africa) then
nationally (the Kenyan experience). In doing this, citations of existing studies and theories should
be properly done to support the problem. Background information is followed by the statement of
the problem and then objectives.
Statement of the problem
This begins with a brief introductory section which introduces briefly the general area of study.
The researcher then narrows down to the specific problem to be studied. A good problem
statement should have the following characteristics / elements.
a) Written clearly and in a way that the reader’s interest is captured immediately
b) The specific problem in the statement is objectively researchable
c) The scope of the problem is indicated
d) The importance of the study in adding new knowledge is stated clearly
e) It should give the purpose of the research which should be stated in specific terms in one or
two sentences within the problem statement
NB: The symptoms of the problem should be manifested in a manner that the reader feels indeed
the study is warranted.
Stating the objectives
Objectives help the researcher to keep to the scope of the study by identifying the area of
knowledge that the researcher is focusing on. In stating the objectives, neutral phrases should be
used and not phrases that are biased or subjective.
Biased / subjective phrases:
To show
To prove
To confirm
To verify
To check
To demonstrate
To indicate

15 of 46
To validate
To explain
To illustrate
Neutral phrases
To determine
To compare
To investigate
To differentiate
To explore
To find out
To examine
To inquire
To establish
To test
Usually, one begins by stating the general objective and then puts down the specific objectives.
The specific objectives should not be so many. Objectives should be S.M.A.R.T. i.e. Specific,
Measurable, Attainable, Realistic and Time bound.
Illustration 1
Title:
INFLUENCE OF RESOURCE MANAGEMENT SKILLS ON THE PERFORMANCE OF SMALL SCALE
AND MEDIUM ENTERPRISES IN RURAL KENYA
General objective:
The purpose of this study is to explore the influence of resource management skills on the
performance of small and medium enterprises in rural Kenya.
Specific objectives:
The specific objectives of the study will be:
a) To identify the influence of social-economics status on the performance of small and
medium enterprises in rural Kenya
b) To investigate the influence of saving practices on the performance of small and medium
enterprises in rural Kenya
c) To investigate the effect of financial management practices on the performance of small
and medium enterprises in rural Kenya
Formulating hypothesis
A hypothesis is a researcher’s prediction regarding the outcome of the study. It states possible
differences, relationships or causes between two variables or concepts. They are derived from or

16 of 46
based on existing theories, previous research, personal observations or experiences. A study can
have one hypothesis or, where the study includes several variables, multiple hypotheses can be
formulated. It is important to give careful thought to the hypothesis because the study revolves
around them. It is the hypotheses that are put to empirical test in a study. The test of a hypothesis
involves collection and analysis of data that may either support or fail to support the hypothesis.
The collected data is analyzed to determine whether the hypothesized relationship exists.
NB: If results fail to support a stated hypothesis, it does not mean that the study has failed. Such a
situation implies that existing theories or principles need to be revised or retested under
various situations.
Depending on the type of research and nature of analysis, one can use research questions instead
of hypotheses. Where research questions are used, words such as how, what or why are used.
However, one should not use both research questions and hypotheses.
Purpose of hypotheses
1) They provide direction.
2) They ensure collection of evidence necessary to answer the questions posed in the
statement of problem.
3) They sensitize the investigator to certain aspects of the situation that are relevant
regarding the problem at hand.
4) They permit the researcher to understand the problem with greater clarity.
5) They guide data collection.
6) They form the framework for the ultimate conclusions as solutions.
Characteristics of good hypotheses
1) They must state clearly and briefly the expected relationship between variables.
2) Should be based on sound rationale derived from theory, previous research or
professional experience.
3) Should be consistent with common sense or generally accepted truths.
4) They must be testable within a reasonable time.
5) Should be related to empirical phenomena i.e. should be tested on results from data
collected and analyzed. Words that suggest moral judgment like - “ought”, “should”,
“bad” – should be avoided.
6) Variables stated in the hypotheses must be consistent with the purpose statement,
objectives and the operationalized variables in the method section.

17 of 46
Types of hypotheses
There are three types of hypotheses
1) Null hypothesis
It is also known as statistical hypothesis. It states that no relationship or difference exists
between two variables. Any relationship or difference between variables or groups is
merely due to chance or error.
2) Alternative non-directional hypothesis
This is also referred to as a research hypothesis. It states that there is a relationship or
difference between variables but the researcher does not know the nature of such
relationship or difference. It is suitable where previous research findings are conflicting or
where a strong rationale to support a predicted relationship does not exist.
3) Alternative directional hypothesis
This specifies the nature of the relationship or difference between variables. This means
that a relationship may be stated as being greater than, less than, increased, decreased,
higher than, lower than etc.
From the previous illustration (Illustration 1), the following hypothesis and research questions can
be formulated.
Hypotheses
The study will answer the following hypotheses.
HO1: Socio-economic status of SMEs in rural Kenya does not influence their performance
HO2: Saving practices of SMEs in rural Kenya do not influence their performance
HO3: Financial management practices of SMEs in rural Kenya do not have any effect on their
performance
The hypotheses above are null hypotheses. Alternative non-directional hypotheses would be as
follows:
HA1: Socio-economic status of SMEs in rural Kenya influences their performance
HA2: Saving practices of SMEs in rural Kenya influence their performance

18 of 46
HA3: Financial management practices of SMEs in rural Kenya have an effect on their
performance
The alternative directional hypotheses would be as follows:
HA1: Socio-economic status of SMEs in rural Kenya greatly influences their performance
HA2: Saving practices of SMEs in rural Kenya increase their performance
HA3: Financial management practices of SMEs in rural Kenya affect their performance greatly
In case research questions are used, the following would be applicable:
1) How does socio-economic status of SMEs in rural Kenya influence their performance?
2) In what ways do saving practices of SMEs in rural Kenya influence their performance?
3) How do financial management practices of SMEs in rural Kenya affect their performance?
LITERATURE REVIEW
This forms chapter 2 of the research proposal and research report. It involves the systematic
identification, location and analysis of documents containing information related to the research
problem being investigated. It is aimed at obtaining detailed knowledge of the topic being
studied. It leads to appreciation and understanding the research already done in one’s area of
interest.
Purpose / Significance of Literature Review
1) To determine what has already been done in relation to the research problem being
studied. This helps the researcher to:
o Avoid duplication
o Form the framework within which the research findings are to be interpreted
o Demonstrate the researcher’s familiarity with existing body of knowledge
2) It helps reveal what strategies, procedures and measuring instruments have been found
useful in investigating the problem in question.
3) It may suggest other procedures and approaches that can be used.
4) It makes the researcher familiar with other studies and thus facilitate interpretation of the
results e.g. results can be discussed in terms of whether they support or contrast previous
findings.

19 of 46
5) In case the researcher had not narrowed down to a topic, literature review will help limit
the research problem and define it better.
6) Approaches that have proved to be futile will be revealed through literature review.
Scope and organization of literature review
The scope of literature review is not definite i.e. there is no formula for arriving at a decision on
when to stop reviewing. However, the following hints can determine the scope of literature review:
o In an area that has been studied for long such that there is a lot of material on it, one
can read only those studies that are reasonably close to one’s research topic.
o In new or little researched areas, any relevant material can be reviewed.
o Not all available materials should be included. Excessive material doesn’t mean great
research information.
o If material already reviewed is constantly reviewed, then literature review can be
abandoned.
When carrying out literature review one should make a list of key words or phrases to guide the
search. Once collected, the literature should be analyzed, organized and reported in an orderly
manner. To achieve this, an outline of the main topics or themes is made in order of presentation.
Decide on the number of headlines and sub-headlines required depending on how detailed the
review is. The literature should be organized in such a way that the more general is covered first
before narrowing down to that which is more specific to the research problem. At the end of the
literature, a brief summary of the literature and its implications can be provided showing the
gaps that the current study proposes to fill. The following points give a summary of the steps
involved in carrying out literature review.
o Familiarity with the library
o Make a list of key words or phrases to guide the review
o Go to the source of literature guided by the key words and phrases
o Summarize the references on cards for easy organization of the literature
o Once collected, organize the literature, analyze it and report it in an orderly manner.
o Make an outline of the main topics or themes in order of presentation
o Analyze each reference in terms of the outline made and establish where it will be
most relevant
o Organize the literature in such a way that the more general is covered first before
narrowing down to the more specific area in the research problem

20 of 46
Sources of literature
The sources of information can be classified into two:
a) Primary sources:
A primary source is a direct description of a research by a person who actually carried
out the research.
b) Secondary source:
Any publication written by an author who was not a direct observer or participant in
the events described.
Review of literature should be based on primary sources as much as possible because secondary
sources may be altered by the writers. Examples of sources of literature include:
o Scholarly journals
o Theses and dissertations
o Government documents
o Papers presented at conferences
o Books
o References quoted in books
o International indices → listings of dissertations and theses from elsewhere.
o Abstracts → list of journal articles with summaries
o Periodicals-journal, magazines and newspapers
o Grey literature → unpublished work
o Microfilms → where old information is stored
o The internet
METHOD SECTION
The method section (commonly known as Methodology) forms chapter 3 of the research proposal
/ research report. It describes the procedures followed in conducting the study. It includes
research design, sampling techniques, data collection, data analysis, assumptions and limitations
of the study and ethical considerations.

21 of 46
Research design
This is the arrangement of conditions for collection and analysis of data in a manner that aims to
combine relevance to the research purpose with economy in procedure. It constitutes the blueprint
for the collection, measurement and analysis of data. The research design may be split into the
following parts:
i) Sampling design → deals with the methods of selecting items to be observed.
ii) Observational design → relates to conditions under which observations are made.
iii) Statistical design → deals with how many items are to be observed and how data
gathered is to be analyzed.
iv) Operational design → deals with techniques by which procedures in the designs
mentioned above can be carried out.
Features of a research design
1) It should specify the sources and type of information / data relevant to the research
problem.
2) It should specify which approach will be used in gathering and analyzing the data.
3) Includes the time and cost budgets.
4) Should be flexible, appropriate, efficient and economical.
Factors to consider in selecting a research design
1) Means of obtaining information.
2) Availability and skills of the researcher and his staff if any e.g. enumerators.
3) Objectives of the problem under study.
4) Nature of the problem under study.
5) Availability of resources; time and money.
Types of research designs
i) Exploratory research design
It is also called Formulative Research. The main purpose of such studies is that of
formulating a problem for more precise investigation. The emphasis is on the discovery of
ideas and insights about a problem. It is an initial research conducted to clarify and

22 of 46
define the nature of the problem so as to ensure that more vigorous, more conclusive
future study will not begin with inadequate understanding of the nature of the problem.
For example, when studying about impacts of inflation in an economy, then exploratory
research would be done to get the basics about inflation first.
ii) Causal / explanatory research design
It’s a non-experimental investigation where the researcher seeks to identify cause and
effect relationship by forming groups of individuals / objects in whom the independent
variable is present or absent at several levels and then determining whether the groups
differ in the presence of the independent variable.
iii) Descriptive and diagnostic research design
Descriptive research is concerned with describing the characteristics of a particular
individual or group e.g. studies concerning specific predictions, narration of facts and
characteristics of individuals, groups or situations. Diagnostic research studies determine
the frequency with which something occurs or its association with something else e.g. studies
concerning whether certain variables are associated.
Sampling Techniques / Designs
Sampling design is a definite plan for obtaining a sample from a given population. It refers to the
technique or procedure the researcher would adopt in selecting / choosing the sample from the
population. When developing the sampling design, the following factors are considered:
o The population / universe to be studied
o Sampling unit → it could be a geographical unit like a county, district etc or a
construction unit like a house or flat or a social unit such as a family, club, school etc.
o Sampling frame / source list from which the sample is drawn. It consists of names of all
items of the universe.
o Sample size → number of items to be selected from the universe.
o Parameters of interest → i.e. specific characteristics of interest.
o Budgetary constraints
o Sampling procedure
Characteristics of a good sample design
1) Should result into a representative sample.

23 of 46
2) Should result in a small sampling error. (Sampling error is the error caused by observing a
sample instead of the whole population. It is the difference between the sample and the
population values.)
3) Should be viable in the context of funds available for the research study.
4) Should be able to control systematic bias. (Systematic bias is a bias in measurement which
leads to the situation where the mean of many separate measurements differs significantly
from the actual value of the measured attribute. It may be caused by imperfect
calibration of the measurement instrument, changes in the environment which interfere with
the measurement process or imperfect methods of observation.)
5) Should be such that the results of the sample study can be applied in general for the
universe / population.
Types of sampling design
There are two main types of sampling designs:
o Non-probability sampling / Biased sampling
o Probability sampling / Random sampling / Chance sampling
Non-probability sampling / Biased sampling
This is used when a researcher is not interested in selecting a sample that is representative of the
population. Most qualitative studies use non-probability samples. The items for the sample are
selected deliberately by the researcher based on possession of the characteristics that the
researcher is interested in. It includes the following sampling procedures:
a) Purposive sampling
b) Snowball sampling → researcher purposively picks some objects who then choose others
whom they know to possess required characteristics.
c) Quota sampling
d) Convenient / accidental sampling → also called volunteer sampling – objects are picked
as or when they become available to researcher.
Probability sampling
It is also known as Random sampling or Chance sampling. In this case, every item of the universe /
population has an equal chance of being included in the sample. The goal is to select a

24 of 46
reasonable number of subjects, objects or cases that represent the entire target population. It is
therefore key in obtaining a representative sample. It provides an efficient system of capturing, in
a small group, the variations or heterogeneity that exists in the target population. It therefore has
minimal or no bias and it allows generalizability to a larger population. The following sampling
techniques fall under probability sampling design.
a) Simple random sampling
b) Stratified random sampling
c) Systematic random sampling
d) Cluster sampling
e) Area sampling → cluster sampling where clusters happen to be geographical sub-divisions
f) Multi-stage sampling
g) Sequential sampling → ultimate sampling size is not fixed in advance but is determined
according to mathematical decision rules on the basis of information yielded as survey
progresses.
Data Collection
This is achieved through the use of data collection instruments. The most commonly used instruments
are:
a) Questionnaires
b) Interview schedules
c) Observational forms
d) Standardized tests
Questionnaires
They are commonly used to obtain important information about the population. Each item in the
questionnaire is developed to address a specific objective, research question or hypothesis of
study. The researcher must also know how information obtained will be analyzed. Questionnaires
have the following two broad categories of questions
1) Structured or closed-ended questions
They are accompanied by a list of all possible alternatives from which respondents select
the answer of their choice. The researcher may not exhaust all possible answers and thus
he provides a category called “others” to take care of the responses not provided.

25 of 46
Example: What type of house do you live in?
Bungalow [ ] Flat [ ] Maisonette [ ] Others [ ]
2) Unstructured or open-ended questions
The respondent is given freedom of response. No responses are provided.
Other than the two categories of questions above, the following two types of questions are also
found in questionnaires:
a) Contingency questions / Filter questions
At times, certain questions are applicable to certain groups of respondents. In such cases,
further questions are needed to get further information from the relevant sub-groups only.
These subsequent questions after the initial questions are called contingency or filter
questions
Example: Have you ever voted in a general election
Yes [ ] No [ ]
If yes, how many times have you voted? ____________________________
b) Matrix questions
These are questions that share the same set of responses. They are common when scales
such as Likert Type Scale are used.
Example: Beside each of the following statements presented below, please indicate, by
putting a tick where appropriate, your level of satisfaction.
QUESTION: How satisfied are you with your:
i) Financial status 1 [ ] 2 [ ] 3 [ ] 4 [ ] 5 [ ]
ii) Quality of life 1 [ ] 2 [ ] 3 [ ] 4 [ ] 5 [ ]
iii) Level of assets 1 [ ] 2 [ ] 3 [ ] 4 [ ] 5 [ ]
iv) Ability to save 1 [ ] 2 [ ] 3 [ ] 4 [ ] 5 [ ]
Key: 1 = Extremely dissatisfied 2 = Dissatisfied 3 = Neutral
4 = Satisfied 5 = Extremely satisfied

26 of 46
Scales used in questionnaires
Rating scales
These are used to measure perception, attitude, values and behavior. Rating scales consist of
numbers and descriptions used to rate or rank the subjective and intangible components in
research. The numerical scale helps to minimize the subjectivity and makes it possible to use
quantitative analysis. The most commonly used rating scale is the Likert scale. It is often used with
matrix questions. The items in likert scale are usually declarative in form. It comprises 5-7
response categories.
Example:
Please circle the number that best describes your feelings about higher institutions of learning
Key:1 = Strongly disagree 2 = Disagree 3 = Neutral 4 = Agree 5 = Strongly agree
1) Higher institutions should be involved in political deliberations
1 2 3 4 5
2) The management of higher institutions of learning should embrace diversity
1 2 3 4 5
Rules for constructing questionnaires
1) List the objectives to be accomplished
2) Determine how information from each question will be analyzed
3) Ensure clarity
4) If a concept has several meanings, provide the intended meaning
5) Use short questions
6) State the items positively and not negatively
7) Avoid ambiguous questions
8) Avoid leading or biased questions
9) Avoid personal and sensitive questions
10)Use simple words that are understandable
11)Avoid questions that assume facts with no evidence. E.g. Have you stopped buying goods
and services on credit?
12)Avoid psychologically threatening questions E.g. Are you worried about the consequences
of a divorce?

27 of 46
Ordering items in a questionnaire
1) Begin with non-threatening, interesting items
2) Very important questions should not be put at the end of a long questionnaire
3) A logical sequence should be used e.g. related items can be grouped together
4) Questions can also be organized according to the themes being studied
5) If the questionnaire is arranged into content sub-sections, each section should be
introduced with a short statement concerning its content and purpose
6) Each questionnaire should have an identification number
Pretesting the questionnaire
The questionnaire should be pretested to a selected sample which is similar to the actual sample
which the researcher plans to use in the study. Subjects in the actual sample should not be used in
the pretest. The number of cases in the pretest should not be very large. The pretest sample is
between 1% and 10% depending on the sample size. Pretesting is important for the following
reasons:
1) Vague questions which do not capture the meaning intended will be identified.
2) Comments and suggestions made by respondents during the pretesting should be
considered and incorporated.
3) Deficiencies in the questionnaire will be revealed e.g. unclear directions, insufficient
space to write responses, wrong numbering etc.
4) To identify if the methods of analysis are appropriate through analysis of the results
obtained in the pretest. This is necessary particularly when dealing with a large study.
Ways of administering the questionnaire
Three methods can be used to administer questionnaires
1) Self administered questionnaires → respondents complete the questionnaires
themselves. The questionnaires are mailed or hand delivered to the respondents.
2) Researcher administered questionnaires → the researcher uses the questionnaire to
interview the respondents especially where respondents are not able to easily
interpret the questions.
3) Use of internet → respondents receive and respond to the questionnaire through
websites or emails.

28 of 46
NB: Every questionnaire should have a cover letter, also called a Letter of Transmittal. The letter
should be signed by the researcher. It contains an adequate brief about the research. It
contains the purpose and significance of the study, a commitment by the researcher to share
results after study, an assurance of confidentiality and anonymity of respondents and
specific deadlines by which the completed questionnaire is to be returned.
Interviews
This is an oral administration of a questionnaire or an interview schedule. It is a face to face
encounter. When conducting interviews, the interviewer should observe the following:
o Be pleasant
o Show genuine interest in getting to know the respondent without appearing like a spy
o Be relaxed and friendly so as to create a good rapport with the interviewee
o Be familiar with the questionnaire / interview guide
o Interact with the respondent as an equal
o Pretest the interview guide / schedule
o Assure the respondent about confidentiality of information given
o Avoid leading questions
o Remain neutral so as to be as objective as possible
Interviews are conducted using an interview guide / schedule. This is a set of questions that the
interviewer asks. The schedule can be:
a) Structured → structured questions with categories of responses
b) Unstructured → the interviewee gives the response of his / her choice. Probing is
used to get deeper information.
c) Semi-structured → there are both structured and unstructured questions
The information during the interview can be collected by note taking or tape recording. Other
than face to face encounter, interviews can also be conducted via telephone.

29 of 46
Observation
With this instrument of data collection, the researcher utilizes an observation checklist /
observation form to record what he or she observes. First, the researcher must define the
behaviors to be observed and then develop a detailed list of behaviors. During data collection,
the researcher checks off each behavior in the list as it occurs.
Reliability and Validity of Instruments
Reliability
This is a measure of the degree to which a research instrument yields consistent results of data
after repeated trials. If an instrument gives different results in different trials, such an instrument is
unreliable. Three types of errors combine to produce inconsistencies in the measurements, which
ultimately affect the reliability of the data collected. These errors are:
o Error due to the inaccuracy of the instrument
o Error due to inaccuracy of scoring by the researcher
o Unexplained error.
In a research study, a reliability coefficient can be computed to indicate how reliable data is. A
coefficient of 0.80 or more implies that there is a high degree of reliability of data. There are
four methods of accessing reliability in data. These are:
1) Test-retest technique → the same instrument is administered twice to the same group of
subjects with a time lapse between the first test and the second test. All initial conditions
must be kept constant.
2) Equivalent-form technique → two equivalent instruments are used. The instruments are
different but they are both used to measure the same concept. The group / subjects to be
used for the test are divided into two groups. One instrument is used on one group then
after some time, maintaining the same conditions, the other form of instrument is used on
the second group.
3) Split-half technique → in this case the instrument is administered to the subjects only once
in one session. The results or the scored items are then divided into two and compared.
4) The internal consistence technique → a reliability coefficient is computed and a high
coefficient implies that there is consistency among the items in measuring the concept of
interest.

30 of 46
Validity
This is the accuracy and meaningfulness of inferences / conclusions which are based on the
research results. It is the degree to which results obtained from the analysis of the data actually
represents the phenomenon under study. It’s therefore concerned with how accurately the data
obtained in the study represents the variables of the study. If such data is a true reflection of the
variables, then inferences based on such data will be accurate and meaningful. Validity can be
internal or external.
Internal validity → depends on the degree to which extraneous variables have been
controlled for in the study.
External validity → refers to the degree to which research findings can be generalized to
populations and environments beyond the sample. If research findings are only
applicable to the sample, the study findings are not externally valid.
NB: To ensure validity of instruments, the researcher should subject the data collection instruments
to a pretest.
Measurement Scales
In studies that yield quantitative data, (i.e. empirical studies) statistical procedures can be used to
analyze the data. The choice of the statistical procedure to be applied is largely determined by
the type of measurement scale used in the operational definition of the variable. There are four
measurement scales used:
1) Nominal scale
It is the lowest level of measurement. Subjects or cases from the sample are grouped
into categories. It simply describes the difference between things by assigning them to
categories. Subjects / cases in each category have some common set of characteristics.
Examples of variables that can be measured at the nominal scale include; sex, race,
marital status, employment status, language, roofing materials, religions etc. For
example, if a variable “marital status” is included in a study, the variable could be
operationalized as:
Married [ ] Divorced [ ] Single [ ] Separated [ ]
Numerals are often assigned to various categories for the purpose of identification. In
the example above, the following numerals could be used:
1 = Married 2 = Single 3 = Divorced 4 = Separated

31 of 46
2) Ordinal scale
This is an improvement of the nominal scale. It is used when one can detect a deferring
degree of the attribute being measured among the subjects. An ordinal scale not only
groups subjects into categories but also ranks them into some order. In this case,
numerals are used to represent relative position or order among the values of the
variables. Examples of variables that can be measured at the ordinal scale include:
social class, military rank etc.
Example: A researcher may want to rate the cost of accommodation amongst given
group of hotels. The researcher may define the criterion of measuring the different
levels of cost and then assign numerals to the various categories in the following
ways:-
3 = Most expensive
2 = Moderately expensive
1 = Least expensive
3) Interval scale
In this scale, numerals assigned to each measure are ranked in order and the intervals
between numerals are equal. The numerals used represent quantities and
mathematical operations of the numerals will yield meaningful values. The
mathematical operations applicable are only additions and deductions. Examples of
interval scale measures include: temperature, test scores such marks scored in an exam
by a sample of students etc. With interval scales, measures of central tendency such as
mean and measures of dispersion such as standard deviation can be applied. In
interval scale, a true zero point does not exist. For example, if one scored a zero in a
statistical test, it does not mean that they have no knowledge of statistics. If
temperature is at zero degrees centigrade, it doesn’t mean absence of temperature.
4) Ratio scale
This is the highest level of measurement and the most precise method of measuring
variables. Ratio scales have all the characteristics of nominal, ordinal and interval
scales. The ratio scale has a true zero point and all mathematical operations can be
applied to yield meaningful values. Most physical objects such as weight, height,
distance, age, area, blood pressure etc can be measured at the ratio scale. With ratio
scale, powerful statistical procedures can be applied. With ratio scale, a zero score
will mean complete absence. For example, zero meters indicate the absence of any

32 of 46
height / distance and zero kilograms indicate the absence of any weight. Therefore,
ratio scale has a true zero point unlike interval scale whose zero point is only
arbitrary.
Data Analysis
Once the questionnaire or other measuring instruments have been administered, the mass of raw
data collected must be systematically organized in a manner that facilitates analysis. If empirical
/ quantitative analysis is anticipated, the responses in the questionnaire will have been assigned
numerical values (codes). The conversion of data into numerical codes is referred to as coding. The
codes represent attributes or measurements or variables. Only one code should be assigned to
each response category and thus the codes should be mutually exclusive. E.g. if responses
anticipated in a question are “Yes” or “No”, one can assign the number 1 to “Yes” and 0 to “No”
or vice versa.
Coding is easier for closed ended questions since the researcher knows the response categories
and can easily provide numerical codes for non numerical responses. For open-ended questions,
the researcher must try to categorize all the responses given and assign numbers to them. The
coded data is then entered into the computer where the numbers representing various categories
are entered. The process of entering the data into the computer is called data entry. Once data
entry has been done, the choice of statistical procedures to use for analysis depends on:-
i) Proposed hypotheses and objectives. For instance, in an exploratory study, descriptive
analysis could be adequate. If hypotheses will be tested, then inferential analysis is used.
ii) The research design used. E.g. for experimental design where various groups are
compared, analysis of variance is used.
iii) Type of measurement scale used to measure variables.
NB: Data analysis is of two types:-
o Descriptive analysis → done using descriptive statistics such as measures of central
tendency (mean, mode, median) and measures of dispersion such as range and
standard deviation.
o Inferential analysis → done using inferential statistics such as regression and
correlation analysis.

33 of 46
Qualitative Data Analysis
This refers to non-empirical analysis i.e. quantifiable data is not used. The researcher is interested
in analyzing information in a systematic way in order to come to some useful conclusions and
recommendations. Qualitative analysis is thus an interpretive mode of inquiry.
Quantitative Data Analysis
Descriptive analysis / Descriptive statistics
This is the first step of data analysis. It enables the researcher to meaningfully describe a
distribution / data set using a few indices or statistics. Descriptive analysis consists of measures of
central tendency and measures of dispersion / variability.
i) Measures of central tendency
The most common ones are: mode, median and mean.
a) Mode
This is the measurement / value that appears most in a set of observations. It is
easily established by inspection. If two modes occur, such a set is called “bimodal”.
In some cases, there is no mode and thus mode cannot be helpful in describing the
distribution in such a case. If more than two modes are observed, then the mode is
said to be ill-defined.
b) Median
This is the middle-most value in a set of observations / data when the observations
are ranked / arranged in order of magnitude i.e. either in ascending or
descending order. If the number of scores / observations is even, then the median
is the average of the two middle scores. The median does not take into account
extreme values (very low or very high values) in a distribution. This is
disadvantageous because no explanation can be given of such values based on
the median. It may also be advantageous if the researcher wants to exclude
extreme scores because these extreme values are known as outliers and they
distort the distribution.
c) Mean
This is the average of a set of scores. It is obtained by summing up all the values /
scores in a distribution and dividing this sum by the total number of scores. It

34 of 46
therefore takes into account each score in the distribution. The mean has the
following properties:
o If equal sized samples are selected from the same population, their means
are likely to be similar to each other than their modes and medians. Thus
the samples will be said to be stable.
o It is the only measure that takes into account all scores in a distribution
including outliers.
o It has a weakness of being pulled towards the outliers.
ii) Measures of dispersion / variability
Measures of central tendency are not sufficient to measure how scores differ among
themselves in magnitude i.e. they are not sufficient to measure dispersion / variability /
spread amongst scores. This is achieved by measures of dispersion. Dispersion / variability
is the distribution of scores around a particular central value. In statistics, the central value
is usually the mean and hence dispersion / variability is the spread of scores around their
mean. Dispersion measures give the researcher information regarding the extent of
individual differences in a given variable. For example, if all variables had the same
value / score, then there would be no need for variability but when variables score
different values amongst individuals, then the researcher is interested in identifying the
differences / variations and explaining them.
Illustration:
Consider the following sets of data:
A: 78, 78, 78, 80, 82, 82, 82,
B: 45, 55, 70, 80, 90, 100, 120
Both sets have the same mean and median but values in A are much closer to their
mean than those in B. Therefore, mean and median cannot explain this variation,
especially the variation in B.
Measures of dispersion include; range, variance and standard deviation.
a) Range
This is the difference between the highest score and lowest score in a distribution.
A small range shows minimal variability while a big range shows more variation

35 of 46
amongst scores. However, range only involves two scores, the highest and the
lowest, thus making it insensitive to other scores in the distribution.
b) Standard deviation and Variance
It is the extent to which scores in a distribution deviate from their mean. It involves
subtracting the mean from each score to obtain the deviation. If these deviations
are squared, summed up and divided by the total number of observations, the
measure obtained is the Variance. If the value of the variance is small, it implies
that there is small variation in the values i.e. the values / scores are close together.
If the value of the variance is high, this implies that there is more variation in the
scores meaning that the scores are more spread out.
The standard deviation is obtained by taking the square-root of the variance. The
bigger the value of standard deviation, the larger the deviation from the mean
indicating greater variability and vice versa. Standard deviation thus considers all
scores in a distribution. It is also very sensitive to outliers, tending to lean towards
the outliers.
Frequency distribution
A distribution can be represented using diagrams / graphs and tables. The commonly used tables
are frequency distribution tables. Frequency distribution tables show the distribution of scores in a
sample for a specific variable. Descriptive measures such as mean and mode (for numerical data)
and percentages can also be included in the frequency distribution data.
Examples:
Frequency distribution of marital status
Scores Frequency (f)
Single 30
Married 60
Divorced 20
Separated 10
Total N = 120

36 of 46
Frequency distribution of a test scores
Scores Frequency (f)
30 3
40 3
45 2
50 6
60 2
80 3
90 1
Total N = 20
Grouped frequency distribution table
Class interval Frequency (f)
20 – 24 10
25 – 29 5
30 – 34 5
35 – 39 12
40 – 44 18
Total N = 50
Frequency distribution tables may be represented graphically and diagrammatically as:
o Histograms
o Frequency polygon
o Bar chart
o Pie chart
Inferential analysis / Inferential statistics
The main purpose of research is to be able to generalize the results from samples to populations.
This is also referred to as inferring. Hypothesis testing techniques are used for this purpose. These
techniques are often referred to as inferential statistics and they constitute inferential analysis.

37 of 46
Inferential statistics deal with inferences about a population based on results obtained from
samples. Inferential statistics are therefore concerned with determining how likely it is for the
results obtained from a sample to be similar to results expected from the entire population. The
choice of statistical procedures to use for inferential analysis depends on the following:
o Size of the sample
o Types of variables (e.g. discrete or continuous variables) and measurement scale
o Types of research design
Statistical procedures for inferential statistics / analysis
a) Correlation → used to analyze the degree of relationship between two variables.
Computation of correlation coefficient (r) yields a statistic that ranges from -1 to +1. The
correlation coefficient tells the researcher:
i) The magnitude of the relationship. The bigger the coefficient (closer to +1 or -1)
the closer the association between variables. A correlation coefficient of zero
means there is no relationship between variables.
ii)The direction of the relationship i.e. whether positive (direct) or negative (indirect
or inverse). A positive coefficient means that as one variable increases, the other
variable also increases and as one variable decreases, the other variable also
decreases. Thus the variables move in same direction. A negative coefficient
means that as one variable increases, the other variable decreases and vice
versa. The variables move in opposite directions.
b) Regression → regression analysis is used to establish the causal-effects of variables i.e.
finding out whether an independent variable predicts / estimates a given dependent
variable. Regression analysis is of two types:
i) Simple regression → used when the researcher is dealing with only one
independent variable and one dependent variable.
ii)Multi regression → used when the researcher is dealing with a group of
independent variables (2 or more) and one independent variable. The
researcher attempts to determine whether the independent variables predict a
given dependent variable.
c) Analysis of variance (ANOVA) → used to determine whether there are significant
differences between two or more groups or samples at a selected level of probability.

38 of 46
d) Chi-square test ( ) → this is used to establish the relationship between two variables
both of which are categorical in nature. E.g. a researcher may want to test the hypothesis
that there is a relationship between gender and number of road accidents caused by
drivers. The variable “gender” is categorized as male and female while the variable
“number of accidents” is categorized as none, few and many.
e) T-test → this is a special case of ANOVA. It is used to test whether there are significant
differences between two means derived from two samples or groups at a specified
probability level.
Logical and ethical issues in research
These are issues that the researcher must be aware of before starting the research as well as
when conducting the research. They help save resources and also ensure high quality work. They
include the following:
Logistical issues
These are processes, actions or activities that a researcher must address to ensure successful
completion of a research. They are divided into 3 categories:-
a) Pre-field logistics. They are:
o Terms of reference → necessary where a consultant is to be hired to do the
research
o Obtaining research permit
o Establishing a work plan
o Training enumerators
o Pre-testing instruments
o Sampling
o Distributing instruments
b) Field-work logistics. They include knowledge on:
o Problems encountered in the field such as transport problems and costs, climate,
language barriers, hostile respondents, areas prone to some diseases, etc.
o Tips on conducting the research
c) Post-fieldwork logistic. These include the process of getting the completed instruments from
the field to the place where data coding and analysis is to be done.

39 of 46
Ethical issues
These deal with the researcher’s conduct and serve as guide to his / her behavior when
conducting research. They include the following:
a) Plagiarism and fraud → plagiarism is a situation where the researcher refers to another
person’s work as theirs without acknowledging the author. Fraud is where the researcher
fakes data that has not actually been collected.
b) Misuse of privileges → e.g. a doctor undertaking certain research tests on the pretext
of providing treatment.
c) Confidentiality and privacy of respondents should be guaranteed.
d) Anonymity → a researcher could disclose the information about an individual but
protect the identity of the person by using numbers, third parties or pseudo names.
e) Physical and psychological harm to respondents should be avoided.
f) Voluntary and informed consent i.e. the respondent should participate in the research
voluntarily.
g) Use of vulnerable and / or special populations → it is unethical to use such populations
without their consent or the consent of their guardians.
Referencing
A researcher acknowledges the input of other authors in his / her work by referencing.
Referencing Within Text
The author’s last name and year of document’s publication are put after a paraphrased
statement in the text. The name and year are put in brackets.
Example:
Among the economic factors that affect satisfaction with quality of life, income has
been found to be positively related to satisfaction with quality of life (Berry and
Williams, 1987).
At times, the author’s name and year may begin the statement. In this case only the year is put
in brackets.

40 of 46
Example:
Berry and Williams (1987) found a positive relationship between income and
satisfaction with quality of life.
Where there are three or more authors, the name of the first author is written followed by the
words “et al.” written in italics. However, in the list of references, all the authors’ names are
indicated.
Example:
Among the economic factors that affect satisfaction with quality of life, income has
been found to be positively related to satisfaction with quality of life (Brown et al.,
2000).
Brown et al. (2000) found a positive relationship between income and satisfaction
with quality of life.
Cited Reference and Bibliography
Towards the end of the proposal and report, the researcher provides a list of references used
in the study. Cited references refer to a list of references which the researcher actually read
and cited in the text. Bibliography refers to the list of materials that were read whether they
were cited or not. The words “Bibliography” and “References” are used synonymously.
The format for writing references varies with universities. Moi University uses the American
Psychological Association (APA) manual format. Other formats include:
o Modern Language Association (MLA) style → year of publication is indicated at the end.
o Library of Congress style.
Referencing Different Sources of Information Using APA Format
1) Journal article – one author
Author, (Year of Publication). Title of the article. Title of the Journal in italics or underlined,
Journal volume number, Journal Number, page(s).

41 of 46
Example:
Moon, M. (1990). Consumer Issues and the Elderly. Journal of Consumer Affairs, No. 24,
235 – 244.
2) Journal article – two authors
Authors, (Year of Publication). Title of the article. Title of the Journal in italics or
underlined, Journal volume number, Journal Number, page(s).
Example:
Hira, K. Tahira and Mugenda, O. M. (1987). Families’ Perception of the Bankruptcy
Process. Family Perspectives, Vol. 21, No. 1, May, 1987.
3) Journal article – more than two authors
Authors, (Year of Publication). Title of the article. Title of the Journal in italics or
underlined, Journal volume number, Journal Number, page(s).
Example:
Palmore, F. B., Fillenbaum, S. S. and George, L. K. (1984). Consequences of Retirement.
Journal of Gerontology, No. 39, 109 – 116.
4) Newspaper article
Author, (Date). Title of the article. Name of the newspaper in italics, page(s).
Example:
Watoro, Kamau (August 9th, 1999). New Campaign on Child Labour. The Daily Nation, pp.
17.
5) A book
Author, (Year of publication). Title of the book. Place of publication, Publisher.
Example:
Haris, H. I. (1970). Principles of Management. San Francisco, CA Bancroft Whitney Co.
6) Chapter, essay or section of an edited book
Author, (Year of publication). Title of the chapter, essay or section. In (Editors). Title of the
book in italics [page(s)]. Place of publication, Publisher.
Example:
Helse, D. R. (2000). Problems in Path Analysis and Causal Inference. In E. F. Borgatta and
G. W. Bohrnstedt (Eds.) Sociological Methodology (pp. 38 – 730). San Francisco,
Jossey-Bass.
7) Journal article from the internet
Author, (Year). Title of the article. Available, Internet: (Website).

42 of 46
Example:
Herz, J. C. (1995, April). Economic Outlook. Available, Internet: www………..
8) Unpublished source such as a thesis, dissertation, papers etc.
Author, (Year). Title. Unpublished Thesis / Dissertation. Place of publication, Publisher.

43 of 46
RESEARCH PROPOSAL & RESEARCH PROJECT REPORT WRITING
Research Proposal Writing
The proposal is written using the future tense since it details an intended activity to be conducted
in the future. The following components make-up a proposal in the following order:
1) Cover page. The cover page has the following details.
 Title
 Author
 Proposal phrase / Report phrase – for the report
A research proposal submitted in partial fulfillment of the requirements for the
award of a _______ in _________ of Moi University
School of ___________ Department of __________
 Date
2) Declaration page
Declaration by candidate:
This ____ is my original work to the best of my knowledge and has not been presented
for the award of a degree in any other University. No part of this _____ may be
reproduced without the prior written permission of the author and / or Moi University.
(Name) …………………………… …………………………
(Admission Number) Signature Date
Declaration by supervisor:
This _____ has been submitted for examination with my approval as a University
Supervisor.
Name,
Moi University.
…………………………………. …………………………………
Signature Date
3) Dedication
4) Table of contents

44 of 46
5) List of tables → the title is written above the left top corner and the author is written
below the bottom left corner of the table and a table should not spill to another page.
6) List of figures → both the title and author should be written below the bottom left corner
of the figure in that order and a figure should not spill to another page.
7) Abbreviations and acronyms
8) Acknowledgements
9) Abstract → this is a one paragraph (not more than 250 words) summary of what the
researcher intends to do. It is unstructured and single spaced. It gives an overview of the
following:
o Brief introduction statement
o Brief problem statement
o General and specific objectives
o Methodology, consisting of:
 Research design
 Population, sampling techniques, sample size
 Data types and sources
 Data collection
 Data analysis
NB: For the research report, the abstract consists of the above plus;
 Key findings
 Key conclusions and recommendations based on results
NB: The aforementioned nine parts are the preliminary pages & have Roman Page
Numbers apart from the cover page which should not have a page number. The rest
of the pages after the preliminary pages should have numerical page numbers.
10)Chapter One: Introduction
1.1 Background information
1.2 Statement of the problem
1.3 General objectives
1.4 Specific objectives
1.5 Research questions or hypotheses
1.6 Justification or Significance of the study
1.7 Area of study
11)Chapter Two: Literature review

45 of 46
At the end of literature review, a conceptual framework for the study is provided. This is a
graphical / diagrammatic representation of how the researcher conceptualizes the
relationship between variables (dependent and Independent) in the study.
Example: From the previous Illustration 1:
“Influence of resource management skills on the performance of small & medium
enterprises in rural Kenya”
Dependent variable → Performance of SMEs
Independent Variables → Socio-economic characteristics, Saving practices and Financial
management practices
The following conceptual framework can be adopted:
12 Chapter Three: Methodology
3.1 Theoretical framework → a researcher should give a brief description of the
theory guiding his study and show how the study in question is related to the
theoretical background. For scientific / inferential analysis, this section is
followed by: empirical models – models used in that kind of study; Evaluation
of the model adopted for the study; Specification of the model.
3.2 Data types and sources
3.3 Research design → including target population, sample size and sampling
techniques used.
3.4 Data collection
3.5 Data analysis
3.6 Ethical considerations
3.7 Limitation of Study (when writing the report after doing the research)
13 References
Socio–economic characteristics
Saving practices
Financial management practices
Performance of
SMEs

46 of 46
14 Appendices – includes:
Questionnaire or interview schedule
Request / approval letter
Budget
Work plan
Any tables and / or figures that are too big to be put in the main body
Research Report Writing
The report is written in past tense since the researcher is now giving an account of what was done
during the research. The report consists of all the aforementioned sections under the proposal with
the appropriate sections adjusted to past tense particularly in chapter one and chapter three.
After chapter three (methodology), the report consists of the following two extra chapters:
1 Chapter Four: Results and Discussions
This is where data is analyzed and results presented and discussed in details. Hypotheses
are also tested.
2 Chapter Five: Summary, Conclusions and Recommendations
5.0 Summary {on model / results}
5.1 Conclusions {on key findings and hypotheses testing}
5.2 Recommendations {based on the findings}
3 Chapter five is followed by:-
References
Appendices

Elements of research methods

More Related Content

What's hot (20)

Similar to Elements of research methods (20)

Recently uploaded (20)

Elements of research methods