Quantitative research methodology and survey design

RESEARCH METHOD II
(Quantitative research/Survey research)
Balela Boru Basaye
Lecturer, Dept. of social anthropology
Bule Hora University, Ethiopia
E-mail:balelaboruu@gmail.com

CHAPTER ONE
WHAT IS QUANTITATIVE RESEARCH?
 OVERVIEW OF SCIENCE AND SCIENTIFIC RESEARCH
METHOD
 Science can be defined as a methodological and systematic approach to
the acquisition of new knowledge.
 Science is ‘‘an objective, logical, and systematic method of analysis of
phenomena, devised to permit the accumulation of reliable knowledge’’
(Lastrucci 1963:6).
o Scientists attempt to gain new knowledge by making careful observations
and using systematic, controlled, and methodical approaches
(Shaughnessy & Zechmeister, 1997).
o Scientific knowledge is based on objective data that were reliably
obtained in the context of a carefully designed research study.
o In short, scientific knowledge is based on the accumulation of empirical
evidence

 The scientific method is an approach to the acquisition of
new knowledge, and this approach effectively distinguishes
science from non-science.
 It is a set of research principles and methods that helps
researchers obtain valid results from their research studies.

 The goals of scientific research, in broad terms, are to answer
questions and acquire new knowledge.
 Most researchers agree that the three general goals of scientific
research are description, prediction, and
understanding/explanation (Cozby, 1993; Shaughnessy &
Zechmeister, 1997).

Definition of research
 Research is defined as the creation of new knowledge and/or
the use of existing knowledge in a new and creative way so as
to generate new concepts, methodologies, and understandings.
 It is a systematic inquiry to describe, explain, predict, and
control the observed phenomenon.
 It involves inductive and deductive methods.
 Inductive methods analyze an observed events, while
deductive methods verify observed events.

Cont…
 Inductive approaches are associated with qualitative
researches.
 Deductive approaches are more commonly associated with
quantitative analysis.
Scientific research is systematic, controlled, empirical, and
critical investigation of natural phenomena guided by theory
and hypotheses about the presumed relations among such
phenomena.
– Kerlinger, 1986
• Research is an organized and systematic way of finding
answers to questions

RESEARCH METHODOLOGY
 The methodology is an outline of the overall data collection and
analysis strategy that will be used to implement the research cycle.
 The methodology should:
 Be compatible with the preliminary data analysis plan
 Be designed in a way that ensures the intended scope of the research
(i.e. objectives and research questions) can be feasibly achieved to
the required quality, given the time, resources and access available
 Designing a methodology involves three key components:
 Selecting the overall research method
 Selecting the appropriate data collection approach(es)
 Designing the sampling strategy

CATEGORIES OF RESEARCH
Qualitative research
 It involves studies that do not attempt to quantify their results
through statistical summary or analysis.
 Qualitative studies typically involve interviews and
observations without formal measurement.
 A case study, which is an in-depth examination of one person,
is a form of qualitative research.
 Qualitative research is often used as a source of hypotheses for
later testing in quantitative research.

 Creswell (1994) defines qualitative research
as ‘’an inquiry process of human
understanding a social or human problems
based on building a complex, holistic picture,
formed with words, reporting detailed views
of informants, and conducted in natural
setting’’.
 It addresses the ‘how’ and ‘why’ research
questions and enables deeper understanding
of experiences, phenomena, and context

Cont…
 Qualitative research can be characterized as the attempt to
obtain an in-depth understanding of the meanings and
'definitions of the situation' presented by informants, rather
than the production of a quantitative 'measurement' of their
characteristics or behavior (Wainwright, 1997).
 Any kind of research that produces findings not arrived at by
means of statistical procedures or other means of
quantification (Strauss and Corbin 1990, pp. 17-18).

Qualitative research…
 The goal of understanding a phenomenon from the point of
view of the participants and its particular social and
institutional context is largely lost when textual data are
quantified (Kaplan and Maxwell, 1994).
 Originally developed in the Social Sciences.
 Have a specific strength in helping to understand people as
well as social and cultural phenomena (Avison, Lau, Myers &
Nielsen,1999).
 Used for describing the participant’s views of processes and
collecting subjective accounts of phenomena.
 Used for analysis of the data, finding connections &
relationships, the influence of the context and different
perspectives toward phenomena.

QUANTITATIVE RESEARCH
 Quantitative research is a research strategy that focuses on
quantifying the collection and analysis of data.
 Quantitative research involves studies that make use of
statistical analyses to obtain their findings.
 It is the process of collecting and analyzing numerical data.
 Key features include formal and systematic measurement
and the use of statistics.
 Deals in numbers, logic, and an objective stance.
 It focus on numeric and unchanging data and detailed,
convergent reasoning.

SURVEY RESEARCH
Survey research is defined as "the collection of information
from a sample of individuals through their responses to
questions" (Check & Schutt, 2012, p. 160).

Cont…
SAMPLING
 A sample is “a smaller (but hopefully representative)
collection of units from a population used to determine
truths about that population” (Field, 2005).
 Why sample?
 Resources (time, money) and workload
 Gives results with known accuracy that can be calculated
mathematically
 The sampling frame is the list from which the potential
respondents are drawn.
 Registrar’s office
 Class rosters

 What is your population of interest?
To whom do you want to generalize your
results?
All doctors
 School children
 Women aged 15-45 years
Other

There are factors that influence sample
representative-ness
Sampling procedure
Sample size
Participation (response)
When might you sample the entire
population?
When your population is very small
When you have extensive resources
When you don’t expect a very high response

Definition of survey research
 Survey research is the most popular and common
research method used in social sciences
 It is one of the most important areas of measurement in
applied social research.
 Survey research is defined as "the collection of
information from a sample of individuals through their
responses to questions" (Check & Schutt, 2012, p. 160).

Cont…
 Survey studies are usually used to find the fact by collecting the data
directly from population or sample.
 The researcher collects the data to describe the nature of existing
condition or look forward the standards against existing condition or
determine the relationships that exists between specific events.
 Survey study intends to understand and explain the phenomena in a
natural setting.
 Compare different demographic groups or see the cause and effect
relationship to make predictions.
 It requires responses directly from respondents of large population
in general
 Survey researches demands various tools to collect the data from
samples. They are ranging from observation, interview to
questionnaire.

CONT…
 Survey research is a quantitative method for
collecting information from a pool of respondents by
asking multiple survey questions.
 Survey Research is defined as the process of
conducting research using surveys that researchers
send to survey respondents.
 The data collected from surveys is then statistically
analyzed to draw meaningful research conclusions.

CONT…
 Survey research is a general term for standardized mass
questioning of a representative sample of individual members
of a population under study.
 Survey research is a popular and powerful means by which to
study people and organizations in society.
 It consists of a rich set of techniques used to obtain
information about individual attitudes, values, behaviors,
opinions, knowledge, and circumstances.

CONT…
 Surveys are also used to study organizations
and institutions, for example, assessing their
culture, policies, and finances.
 A social survey is a standardized and
systematic method for obtaining information
about a population by using a questionnaire to
measure elements sampled from that
population

 To conclude, Survey research is a method of data collection
that involves gathering information from a sample of
individuals through the use of questionnaires or interview.
 It is a widely used research technique in various fields,
including social sciences, marketing, psychology, and public
health.
 Survey research can provide valuable insights and help
researchers understand opinions, attitude, behaviors, and
trends within a specific population.

CONT…
 The purpose of survey research design is to discover the
relative incidence, distribution, and inter-relations
of sociological and psychological variables.
(Kerlinger,1986)
 Survey research is defined as "the collection of information from a
sample of individuals through their responses to questions"
(Check & Schutt, 2012)
 The survey method gathers data from relatively
large number of cases at a particular time.
(Boudah,2011)

Steps in Survey Research design
1. Defining the purpose and objective of the study i.e. the
problem, why to conduct a research and what is its worth, the
clear objectives formulation etc. are included in the first step of
survey research.
2. Selecting and defining the target population, i.e. upon which
the study is based.
3. Choosing and selecting techniques for data gathering. (i.e.
the instrument like interview, questionnaire etc. to be used for
data collection). The selection of instrument depends upon the
cost, applicability and the research design.
4. A major and good representative (sample) of the
population is to be taken (i.e. this is the step of sampling).

Cont…
5.The process of data gathering (or simply the step of
executing the research), where the interviews, questionnaires or
any other instrument is used for which the questions are pre
designed.
6.The questionnaire (if used) is then followed up. The
questions asked from the interviewee are answered, evaluated
and hence the process of data gathering is completed.
7.The data gathered is processed, analyzed, and interpreted,
from which the results are concluded and the findings are then
generalized.
8.The whole study is then presented in the form of research
report (called survey report) for the purpose of transmission and
further study.

TYPES OF SURVEY RESEARCH
1. Cross-sectional surveys
o Cross-sectional survey are conducted at a single point in
time to gather information from a representative sample of
individuals.
o This types of survey provides a snapshot of the
populations characteristics, attitudes, or behaviors at a
specific moment.

Cont…
 Cross-sectional studies, also known as one-shot or status studies
 The most commonly used design in the social sciences.
 This design is best suited to studies aimed at finding out the
prevalence of a phenomenon, situation, problem, attitude
or issue, by taking a cross-section of the population.
 They are useful in obtaining an overall ‘picture’ as it stands at the
time of the study.
 They are ‘designed to study some phenomenon by taking a cross-
section of it at one time’
Eg;The attitude of the community towards equity issues

Cont…
2. Longitudinal surveys
o Longitudinal surveys involve collecting data from the same
sample of individuals over multiple time points.
o This allows researchers to study changes, trends, or
developments in attitudes, behaviors, or other variables over
time.
o Used to measure changes in one or more measured
characteristics of a populations.

 Longitudinal surveys, can be further
classified into three distinct types of
longitudinal designs (trend, cohort, and
panel).
a) Trend studies
 Focus on the same population of people
Use opinion poll surveys to look at their attitudes over time.
 While the population is always the same trend studies select
samples from that population.
Analyze trend of a phenomenon
 Eg; survey of graduates preferring mobile learning

b) Cohort research
 A specific population is studied repeatedly as well.
This studies center around how given groups with a common
characteristic view social phenomena
Cohort studies are longitudinal, which means they monitor the
effects of a treatment over time.
cohort studies are used to examine the effectiveness and
outcome of a intervention program.
 Eg; to determine the effectiveness of
the new Core curriculum.

Cont…
C) Panel survey
o Panel surveys are a specific type of longitudinal survey where
the same individuals are surveyed repeatedly over time.
o Sampling a cross-section of individuals.
o It can be useful for studying individual level changes, tracking
behaviors, or understanding the effects of interventions or
policies.

Example of pannel survey
 A high school seniors studied in 2020, will be the
same population studied in 2022, after 2 year
graduation, and after 2024 .

Cont…
3. Cross-cultural surveys
o It aim to compare attitudes, beliefs or behaviors
across different cultures or countries.
o These surveys often involve adapting survey
instruments to account for cultural differences
and ensure comparability across groups.
 These above mentioned classifications of
surveys are few examples of survey research
methods.

Cont…
 The choice of survey method depends on
factors such as the research objectives, target
population, available resources, and practical
considerations.
 Each method has its own limitations, and
researchers should select the most
appropriate method based on their specific
research needs.

Cross-sectional vs longitudinal survey
method

Characteristics of survey research
The following are the main characteristics of the survey
method of research:
1. The survey method gathers data from a relatively large
number of cases at a particular time.
2. It is essentially cross-sectional.
3. It is not concerned with the characteristics of individuals.
4. It involves clearly defined problem.
5. It requires experts imaginative planning.
6. It Involves definite objectives.
7. It requires careful analysis and interpretation of the data
gathered.

Cont…
8. It requires logical and skillful reporting of the findings.
9. Surveys vary greatly in complexity.
10. It does not seek to develop an organized body of scientific
principles.
11. It provides information ‘useful to the solution of local
problems.
12. It contributes to the advancement of knowledge because
affords penetrating insight into the nature of what one is dealing
with.
13. It suggests the course of future developments.
14. It determines the present trends and solves current
problems.
15. It helps in fashioning many tools with which we do the
research

ADVANTAGES OF SURVEY METHOD
 It permits wide coverage at a minimum expense of both
money and effort.
 It affords wider geographical coverage it makes for greater
validity in the results through promoting the selection of a
large and more representative sample.
 The validity of questionnaire data also depends in a crucial
way on the validity and willingness of the respondent to
provide the information requested.
 Research has shown that respondents are as a group of
superior intelligence.

Cont…
 It gives the opportunity to researcher to see the reality more
closely.
 Survey research design ensures greater objectivity.
 It helps to know the social situation.
 The important aspect of survey study is its versatility. It is the
only practical way to collect many types of information from
individuals, such as personal characteristics, socio-economic
data, attitudes, opinions, experiences and expectations.
 Facilitates to draw generalizations about population on the
basis of data from representative sample.
 It is flexible and allows various methods of collection of data.
 It sensitizes the researcher to unanticipated or unknown
problems.

DISADVANTAGES OF SURVEY METHOD
 The possibility of the misinterpretation of the questions.
 Misinterpretations are due to the respondent’s willingness or
impersonality.
 The reliability of the questionnaire is often ignored.
 It requires training for those who collect information, which
demands more financial source.
 It is time consuming process, if the universe is large.
 Its reliability and validity is based on the honesty and
efficiency of the researcher.

Cont…
 Survey mostly based on samples, so always there is a
possibility of sampling error.
 As data is collected from primary sources, the feasibility is
depends upon the willingness and cooperation of the
respondents.
 There is a possibility of response error, due to respondents’
untrue / misleading answers.

CHAPTER TWO
MEARING CONCEPTS AND VARIABLES
MEASUREMENT
 Measurement is the process by which we describe and ascribe
meaning to the key facts, concepts, or other phenomena that
we are investigating.
 Kaplan identified three categories of things that social
scientists measure including observational terms, indirect
observables, and constructs.
 Measurement occurs at all stages of research.

Cont…
 In quantitative research, measurement refers to the process of
assigning numerical values to variables or attributes of interest
in order to gather objective and quantifiable data.
 It involves developing reliable and valid instruments or
procedures to collect data in a systematic and standardized
manner.
 It allows researchers to quantify and analyze variables,
relationship, and patterns.

Cont…
 It enables researchers to make comparisons, identify trends,
and draw statistical inferences.

CONCEPTUALIZATION
 Conceptualization is a process that involves coming up with
clear, concise definitions.
 It involves writing out clear, concise definitions for our key
concepts.
 Conceptual definitions are abstractions, articulated in words,
that facilitate understanding.

Cont….
 Conceptual definitions are at their most powerful when they
are linked together to build theories that explain research
results.
 Conceptual definitions are at their weakest in the conduct of
research itself, because concepts have no empirical basis—we
have to make them up to study them.
 There are three things one wants to do in any science:
(1) describe a phenomenon of interest;
(2) explain what causes it; and
(3) predict what it causes.

Operationalization
 Operational definitions consist of a set of instructions on how
to measure a variable that has been conceptually defined.
 Operationalization is the process by which we spell out
precisely how a concept will be measured.
 It involves identifying the specific research procedures we will
use to gather data about our concepts.

Cont…
 Operationalization works by identifying specific indicators that
will be taken to represent the ideas that we are interested in
studying.
 If, for example (1), we are interested in studying masculinity,
indicators for that concept might include some of the social
roles prescribed to men in society such as breadwinning or
fatherhood. Being a breadwinner or a father might therefore be
considered indicators of a person’s masculinity.

Cont…
 Let’s look at another example (2) of indicators. Each day,
Gallup researchers poll 1,000 randomly selected Americans to
ask them about their well-being. To measure well-being,
Gallup asks these people to respond to questions covering six
broad areas: physical health, emotional health, work
environment, life evaluation, healthy behaviors, and access to
basic necessities. Gallup uses these six factors as indicators of
the concept that they are really interested in.

Levels of Measurement
 Whenever you define a variable operationally, you do so at
some level of measurement.
 Most social scientists recognize the following four levels of
measurement, in ascending order: nominal, ordinal, interval,
and ratio.
Nominal Variables
 A variable is something that can take more than one value. The
values of a nominal variable comprise a list of names

 You can list religions, occupations, and ethnic groups; and you
can also list fruits, emotions, body parts, things to do on the
weekend, baseball teams, rock stars . . . the list of things you
can list is endless.
Think of nominal variables as questions, the answers to which
tell you nothing about degree or amount.
o What’s your name?
o In what country were you born?
o Are you healthy?
o On the whole, do you think the economy is in good shape?
o Is Mexico in Latin America?
o Is Bangladesh a poor country?
o Is Switzerland a rich country?

 The following survey item is an operationalization of the
nominal variable called ‘‘religious affiliation’’: 26a.
Do you identify with any religion? (check one)
□ Yes □ No
If you checked ‘‘yes,’’ then please answer the following
question.
What is your religion? (check one):
□ Protestant
□ Catholic
□ Jewish
□ Moslem
□ Other religion
□ No religion

Ordinal Variables
 Like nominal-level variables, ordinal variables are
generally exhaustive and mutually exclusive, but they
have one additional property: Their values can be rank
ordered.
 Any variable measured as high, medium, or low, like
socioeconomic class, is ordinal.

Cont…
 The three classes are, in theory, mutually exclusive and
exhaustive.
In addition, a person who is labeled ‘‘middle class’’ is lower in
the social class hierarchy than someone labeled ‘‘high class’’
and higher in the same hierarchy than someone labeled ‘‘lower
class.’’
 What ordinal variables do not tell us is how much more.

Cont…
 Scales of opinion—like the familiar ‘‘strongly agree,’’
‘‘agree,’’ ‘‘neutral,’’ ‘‘disagree,’’ ‘‘strongly disagree’’ found
on so many surveys—are ordinal measures.
 They measure an internal state, agreement, in terms of less
and more, but not in terms of how much more.

Interval and Ratio Variables
 Interval variables have all the properties of nominal and
ordinal variables.
 They are an exhaustive and mutually exclusive list of
attributes, and the attributes have a rank-order structure.

Cont…
 Ratio variables are interval variables that have a true zero
point—that is, a 0 that measures the absence of the
phenomenon being measured.
 The Kelvin scale of temperature has a true zero: It identifies
the absence of molecular movement, or heat.

Validity and Reliability
 Reliability is a matter of consistency.
 Validity is a matter of social agreement.
 Validity refers to the accuracy and trustworthiness of
instruments, data, and findings in research.
 Nothing in research is more important than validity.
 The validity of data is tied to the validity of instruments.
o If questions asking people to recall their behavior are not valid
instruments for tapping into informants’ past behavior, then
the data retrieved by those instruments are not valid, either.

 Reliability refers to whether or not you get the same answer
by using an instrument to measure something more than once.
 Like all other kinds of instruments, some questions are more
reliable for retrieving information than others.
 If you ask 10 people ‘‘Do the ancestors take revenge on people
who don’t worship them?’’ don’t expect to get the same
answer from everyone.
 ‘‘How many brothers and sisters do you have?’’ is a pretty
reliable instrument (you almost always get the same response
when you ask a person that question a second time as you get
the first time), but ‘‘How much is your parents’ house
worth?’’ is much less reliable. And ‘‘How old were you when
you were toilet trained?’’ is just futile.

CHAPTER THREE
SAMPLING METHODS
LEARNING OBJECTIVES
Learn the reasons for sampling
Develop an understanding about different sampling methods
Distinguish between probability & non probability sampling
Discuss the relative advantages & disadvantages of each sampling
methods

Cont…
 A sample is “a smaller (but hopefully representative)
collection of units from a population used to determine
truths about that population” (Field, 2005)
 Why sample?
 Resources (time, money) and workload
 Gives results with known accuracy that can be calculated
mathematically
 A sampling method is a technique used to select a subset, or
sample, from a large population.

Sampling...
 What is your population of interest?
 To whom do you want to generalize your results?
 All doctors
 School children
 Ethiopian
 Women aged 15-45 years
 Other

Sampling...
The three factors that influence sample
representative-ness
 Sampling procedure
 Sample size
 Participation (response)

Sample size
 Sample size refers to the number of observations
included in a study or experiment.
 It is a crucial factor in research design and statistical
analysis because it affects the reliability and
generalizability of the results.
 Determining the appropriate sample size depends on
the research objectives, population size, statistical
power, the expected effect size.
In qualitative research, sample size is often
determined based on the principle of data saturation,
where data collection continues until new information
or insights stop emerging from the analysis.

Sampling procedure
 The sampling procedure refers to the specific steps or
methods used to select and recruit participants for a research
study.
 The goal of sampling procedure is to obtain a representative
sample that accurately reflects the characteristics of the
larger population under investigation.
Example;
 Random sampling
 Convenience sampling
 Purposive sampling
 Systematic sampling...etc.

Sampling…
SAMPLE
STUDY POPULATION
TARGET
POPULATION

Types of Samples
Probability (Random) Samples
 Simple random sample
 Systematic random sample
 Stratified random sample
 Multistage sample
 Cluster sample
Non-Probability Samples
 Convenience sample
 Purposive sample
 Quota

Process
 The sampling process comprises several stages:
 Defining the population of concern
 Specifying a sampling frame, a set of items or events possible to
measure
 Specifying a sampling method for selecting items or events from
the frame
 Determining the sample size
 Implementing the sampling plan
 Sampling and data collecting
 Reviewing the sampling process

Population definition
 A population; can be defined as including all people or
items with the characteristic one wishes to understand.
 Because there is very rarely enough time or money to
gather information from everyone or everything in a
population, the goal becomes finding a representative
sample (or subset) of that population.

SAMPLING FRAME
 Sampling frame refers to a list or representation
of target population from which a sample is drawn.
 It is a crucial component of the sampling process
as it provides the basis for selecting the sample and
ensures that every individual or element in the
population has a chance of being included.
 The sampling frame should accurately and
completely represent the population being studied.

PROBABILITY SAMPLING
 A probability sampling is one in which every unit in the
population has a chance (greater than zero) of being selected
in the sample, and this probability can be accurately
determined.
 When every element in the population does have the same
probability of selection, this is known as an 'equal probability
of selection' (EPS) design.
 Such designs are also referred to as 'self-weighting' because all
sampled units are given the same weight.

Cont…
 Probability sampling is a method of selecting a
sample from a population in such a way that each
member of the population has a known and non-
zero probability of being included in the sample.
 It involves using random selection techniques to
ensure that every individual or element in the
population has an equal chance of being selected
for the sample.
 The goal of probability sampling is to obtain a
representative sample that accurately reflects the
characteristics of the population being studied.

TYPES OF PROBABILITY SAMPLING
Probability sampling includes:
 Simple Random Sampling,
 Systematic Sampling,
 Stratified Random Sampling,
 Cluster Sampling
 Multistage Sampling.

1. SIMPLE 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.

Cont…
Disadvantages
 If sampling frame large, this method impracticable.
 Minority subgroups of interest in population may not be
present in sample in sufficient numbers for study.

2. SYSTEMATIC SAMPLING
 Systematic sampling 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').

Systematic sampling procedure
Assign a number to every population
member.
Select a random number.
Select sample members at regular
interval.

Example of systematic sampling

SYSTEMATIC SAMPLING……
ADVANTAGES:
 Sample easy to select
 Suitable sampling frame can be identified easily
DISADVANTAGES:
 Sample may be biased if hidden periodicity in population
coincides with that of selection.
 Difficult to assess precision of estimate from one survey.

3. 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.
 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.

Cont…
 It is a sampling method in which a researcher
divided population into subgroups and take
sample from each subgroups.
 Member of subgroups have similar characteristics.

STRATIFIED SAMPLING……
 Finally, since each stratum is treated as an independent
population, different sampling approaches can be applied to
different strata.
Drawbacks to using stratified sampling.
 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.

STRATIFIED SAMPLING……
o Draw a sample from each stratum

4. CLUSTER SAMPLING
 Cluster sampling 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.

Cont…
 It is a sampling methods in which a researcher classify
the population into sections and randomly select one
or more cluster or section from the group.
 Member of subgroup have similar characteristics.

CLUSTER SAMPLING…….
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.
 Often used to evaluate vaccination coverage.

CLUSTER SAMPLING…….
• Identification of clusters
– List all cities, towns, villages & wards of cities with their
population falling in target area under study.
– Calculate cumulative population & divide by 30, this
gives sampling interval.
– Select a random no. less than or equal to sampling
interval having same no. of digits. This forms 1st
cluster.
– Random no.+ sampling interval = population of 2nd
cluster.
– Second cluster + sampling interval = 3th cluster.
– Last or 30th cluster = 29th cluster + sampling interval

Difference Between Strata and Clusters
 Although strata and clusters are both non-overlapping subsets
of the population, they differ in several ways.
 All strata are represented in the sample; but only a subset of
clusters are in the sample.
 With stratified sampling, the best survey results occur when
elements within strata are internally homogeneous.
 However, with cluster sampling, the best results occur when
elements within clusters are internally heterogeneous

5. Multistage sampling
 Multistage sampling is a sampling technique commonly
used in survey research and statistical analysis.
 It is method of sampling that involves dividing the
populations into multiple stages or levels, with each
stage representing a subset of the population.
 A sample is drawn at each stage until the desired sample
size is achieved.
 It is often employed when the target population is large
and geographically dispersed.

Group discussion
1. What is the between stratified and cluster sampling?
2. How does sample of the study population is drawn in
each sampling methods.
3. How to determine sampling size, sampling interval and
sampling error in sampling process?
4. What does population mean it the context of sampling
method?

NON-PROBABITY SAMPLING
 Non-probability sampling is where the researcher’s knowledge
and experience are used to create samples.
 Because of the involvement of the researcher, not all the
members of a target population have an equal probability of
being selected to be a part of a sample.
 The difference between nonprobability and probability
sampling is that nonprobability sampling does not involve
random selection and probability sampling does.

There are five non-probability sampling:
1. Convenience sampling: In convenience sampling, elements
of a sample are chosen only due to one prime reason: their
proximity to the researcher.
 These samples are quick and easy to implement as there is
no other parameter of selection involved.
 Involves selecting samples based on convenience.
 It is common used method in research studies, especially in
situation where time, resource, or access to the target
population are limited.

Cont…
2. Quota sampling: Using quota sampling, researchers can select
elements using their knowledge of target traits and personalities
to form strata.
 Members of various strata can then be chosen to be a part of the
sample as per the researcher’s understanding.
 It means to take of a very tailored sample that’s in proportion to
some characteristics or trait of a populations.
 It involves dividing the populations into subgroup or strata
based on certain characteristics, such as age, gender,
occupation, or geographical location.
 The researcher then sets quota for each subgroup based on its
proportion in the populations.

Cont…
3. Snowball sampling:
 Snowball sampling, also known as chain referral or network
sampling, is a non-probability sampling technique used in
research studies, particularly when it is difficult to access or
locate a specific population or when the population is small or
hidden.
 Snowball sampling is conducted with target audiences, which
are difficult to contact and get information.
 It is popular in cases where the target audience for research is
rare to put together.
 Select sample and ask them to refer them to refer you to
others.

Cont…
4. Consecutive sampling: is quite similar to convenience
sampling, except for the fact that researchers can choose a single
element or a group of samples and conduct research
consecutively over a significant period and then perform the
same process with other samples.

 It also known as judgmental or selective sampling, is
non-probability sampling technique commonly used in
qualitative research methods.
 It involves selecting specific individuals or cases that
possess certain characteristics or qualities that are
relevant to the research study.
 In purposive sampling, the researcher deliberately
chooses participants who can provide rich and
meaningful information related to the research
objective.
 It is particularly useful when the researcher aims to
gain in-depth insights, explore specific phenomena, or
target a secific population or subgroup.

CHAPTER FOUR
Data Gathering instruments in
quantitative research

Questionnaire
What is a questionnaire?
 A questionnaire is a set of questions to be asked from
respondents in an interview, with appropriate instructions
indicating which questions are to be asked, and in what
order.
 Questionnaires are used in various fields of research like
survey research and experimental design.

What is a questionnaire? ….
 A questionnaire is a self-report data-collection instrument
that each research participant fills out as part of a research
study.
 Researchers use questionnaires so that they can obtain
information about the thoughts, feelings, attitudes, beliefs,
values, perceptions, personality, and behavioral intentions
of research participants.
 In other words, researchers attempt to measure many
different kinds of characteristics using questionnaires.

What is a questionnaire? …
 A tool for collecting information to describe,
compare, or explain an event or situation, as well
as, knowledge, attitudes, behaviors, and/or socio-
demographic characteristics on a particular target
group.
 A questionnaire is a research instrument that
consists of a set of questions or other types of
prompts that aims to collect information from
a respondent.
 A research questionnaire is typically a mix
of close-ended questions and open-ended

What is a questionnaire? …
 A questionnaire is a list of questions or items
used to gather data from respondents about their
attitudes, experiences, or opinions.
 A questionnaire is a form prepared and
distributed to secure responses to certain
questions.
 It is a tool for obtaining response to
questions by using a form which the respondent
fills by himself.

 A questionnaire serves four functions—
o Enables data collection from respondents.
o Lends a structure to interviews.
o Provides a standard means for writing down answers, and
o Help in processing collected data.

The Questions
 Are the focus on any survey or
questionnaire.
 It is crucial to know how to ask the
questions in written and spoken form.
 The way you ask the questions determines
the answers.

Why use a questionnaire?
Questionnaires are often used to obtain
information from a group of people.
We use them because questions can be targeted
to get the information you need.
They can also be done in several ways;
oBy post or mail
oBy phone
oFace to face

What makes a good
questionnaire?
Order
Start with basic details and move on to more difficult
questions.
Clear questions
Simple language, appropriate to the age of the people
answering the questions.
Relevant to what you are investigating.
Not Personal
Try and avoid questions that need very personal or
embarrassing answers.

What makes a good questionnaire?
Easy to answer
Open questions – allow people to write anything.
Closed questions – restrict answers by giving
options.
Keep answer boxes clear and simple and don’t have
gaps or overlaps.
Avoid bias
Don’t ask questions that push people towards an
answer. Starting a question with;
isn’t it true that…? or don’t you agree that…?
is trying to make people say what you want.

Types of questions in questionnaire
1. Open ended questions in questionnaire
o An open-ended question is a type of research question that
does not restrict respondents to a set of predetermined answers.
o Rather, respondents are allowed to fully articulate their
thoughts, opinions, and experiences as long-form and short-
form answers including paragraphs, essays, or just a few
sentences.
o They are also known as free-form survey questions because
they do not restrict the respondents to a small pool of possible
answer-options.
o Open-ended questions encourage the research participants to
freely communicate what they know and how they feel about
the subject matter.

Open ended questions
 In this types of a questionnaires, the respondents are
free to express their thought freely.
 For instance; what recommendations would you give to
improve online learning.

Generally used for qualitative research
Not a checklist; there are no boxes to tick
Data analysis is more complex because there
are not standard answers

 Use open-ended questions in your questionnaire when you
want to collect qualitative responses for your research.
 They also provide better context for the research data by
helping you to see things from a respondent’s point of
view.
Advantages of Open-Ended Questions
 It helps you to gather detailed information from
respondents.
 Open-ended questions have an infinite possibility of
responses which supports variation in your research data.

Disadvantages of Open-ended Questions
 Responding to open-ended questions is time-consuming and
respondents can easily abandon the questionnaire along the
way.
 It is very difficult to statistically interpret the data collected via
open-ended questions. This makes open-ended questions
highly unsuitable for quantitative data collection.
EX. Open-ended Question Samples
 What is the most important lesson you’ve learned so far?
 What do you think about our new logo?
 How does our product help you to meet your goals?

2. Close Ended Questions
 A close-ended question is one that limits possible
responses to options like Yes/No, True/False, and the
likes.
 It comes with pre-selected answer options and requires
the respondent to choose one of the options that closely
resonates with her thoughts, opinion, or knowledge.
 Close-ended questions are best used in quantitative
research because they allow you to collect statistical
information from respondents.
 If you want to gather a large amount of data that can be
analyzed quickly, then asking close-ended questions is
your best bet.
 Usually utilized to generate statistics for quantitative
research

Advantages of Close-ended Questions
 Close-ended questions are easy and quick to answer.
 It is cheaper to collate and analyze the responses to
close-ended questions.
Disadvantages of Close-ended Questions
 It limits the amount of information that respondents can
provide in your questionnaire.
 It can result in survey response bias as respondents
can be influenced by the options listed in the
questionnaire.

Close-ended Question Samples
1. How do you start your day?
 With coffee
 With exercises
 With meditation
2. What is your favorite genre of music?
 Reggae
 Blues
 Afro-pop
 Rap

Types of questionnaire
1. Structured questionnaires
 Include pre-coded questions with well-defined skipping
patterns to follow the sequence of questions.
 Most of the quantitative data collection operations use
structured questionnaires.
 Fewer discrepancies, easy to administer consistency in
answers and easy for the data management are advantages
of such structured questionnaires.
 Structured questionnaire is a research instrument
consisting of predetermined set of questions designed to
collect specific data or information from respondents.

Cont…
2. Unstructured questionnaires
 Include open-ended and vague opinion-type
questions.
 Maybe questions are not in the format of
interrogative sentences and the moderator or the
enumerator has to elaborate the sense of the
question.
 Focus group discussions use such a questionnaire.

Factors determining the success of a questionnaire
 Response Rate: Refers to how many questionnaire
have been returned.
 Completion rate: refers to how many questionnaire
have been fully completed.
 Validity of response: refers to how honest and
accurate are the responses in the questionnaire.

STEPS IN CONSTRUCTING QUSTIONNAIRE
 There are nine steps involved in the development of a
questionnaire:
1. Decide the information required.
2. Define the target respondents.
3. Choose the method(s) of reaching your target
respondents.
4. Decide on question content.
5. Develop the question wording.
6. Put questions into a meaningful order and format.
7. Check the length of the questionnaire.
8. Pre-test the questionnaire.
9. Finalize the questionnaire
10. Distribute questionnaire
11. Analyze the responses

Cont…
 #1: Identify your research aims and the goal of your
questionnaire
 What kind of information do you want to gather with your
questionnaire? What is your main objective?
 Clearly establish what information you want to gather from
the questionnaire.
 Identify the purpose, goals, and specific research objectives to
guide the design process.
 Determine what specific information you want to collect and
the purpose behind it. This will guide the entire questionnaire
construction process.

Cont…
#2: Define your target respondents
 Clearly, you can’t test everyone – it’s rather plausible that there
have to be certain restrictions with respect to the target
audience of your questionnaire.
 The selection of groups is a key factor for maximizing the
robustness of your study.
 Determine the demographic or specific group you want to
survey.
 Consider factors such as age, gender, location, occupation, or
any other relevant characteristics that help you understanding
your target audience better.

Cont…
 #3: Choose the method(s) of reaching your target respondents.
 There’s a wide variety in how to phrase questions. In
explorative questionnaires, you will find mainly open
questions, where participants can fill in any answer (this
makes sense whenever you try to gain an understanding
of the topics associated with your research question).
 By contrast, quantitative questionnaires primarily include
closed-questions, which have been predefined by the
researcher either in form of multiple choice answers or
rating scales

Cont…
 Choose the appropriate survey method based your
target audience and objectives.
 Common methods include online survey, paper based
surveys, face to face survey, interviews, phone
interviews, or combination of methods.

Cont…
 #4: Decide on question content.
After optimizing each question separately it is time to
improve the overall flow and layout of the
questionnaire.
 Are there transitions from one question to the next?
Are follow-up questions placed correctly?
 Develop a clear and logical structure for your
questionnaire.
 Start with introduction that explains the purpose and
importance of the survey.
 Divide the questionnaire into sections or topics,
ensuring a logical flow of questions.

Cont…
o #5 Develop the question wording
o It refers to the process of creating clear, concise, and effective
language for the questions in your questionnaire.
o It involves carefully crafting the wording of each question to ensure
that respondents understand what is being asked and can provide
accurate and meaningful responses.
o When developing the wording for your questionnaire questions, it’s
important to ensure that they are clear, unambiguous, and easy for
respondents to understand.

Cont…
When develop the question wording, researcher should be;
• use simple and concise language.
• Be specific and avoid ambiguity.
• Avoid double-barreled questions.
• Provide clear response.
• Consider the respondent’s perspective.
• Pilot test and revise.

Cont…
#6 Put questions into a meaningful order and format.
To put questions into a meaningful order and format within a
questionnaire, consider the following guideline;
o Introduction: began with an introduction that provides an overview
of the survey’s purpose and assures respondents about the
confidentiality and anonymity of their response.
o Demographic information: start with questions that gather basic
demographic information about the respondents, such as age,
gender, education level, occupation, income, and location.
o Warm-up questions: Begin with easy and non-sensitive questions
to help respondents get confortable with the survey. These questions
can be general and unrelated to the main topic of the survey.
o Main questions: Arrange the main questions in a logical and
progressive order. Start with broader, more general questions and
then move towards more specific or detailed questions.

o Sensitive questions or personal questions: place sensitive or
personal questions towards the middle or end of the
questionnaire. By this point, respondents may feel more
confortable and open to answering such question.
o Open-ended questions: Include open-ended questions
towards the end questionnaire. This allows respondents to
provide detailed and subjective responses without feeling
overwhelmed at the beginning. Open-ended questions often
require more time and effort to answer, so placing them
towards the end helps to maintain respondents engagement.

Cont…
 # 7 check length of the questionnaire
 Check the length of the questionnaire is important to
ensure that it is an appropriate length for your
respondents.
 A questionnaire that is too long may lead to
respondent fatigue, decreased response rates, or
incomplete responses.
 The ideal length of a questionnaire will vary
depending on specific research context and the
characteristics of your target respondents.
 Striking a balance between collecting necessary
data and respecting respondents’ time and effort is
crucial for obtaining high quality response.

Cont…
#8: Pre-test the questionnaire
 This stage is crucial for evaluation and optimization
purposes. Any questionnaire should be handed to a
representative sample of your target audience before you
go further with it.
 During piloting, you can identify issues in readability and
understanding, in phrasing and overall arrangement.
 It could be helpful to discuss the questionnaire with pilot
participants to better understand their experience. Also,
keep in mind to evaluate your pilot data statistically to
make sure that the analytic procedures of interest truly
can be applied to the data.

Cont…
 Pre-testing questionnaire is an essential step in the survey
research process.
 It involves conducting a trail run of the questionnaire with a
small group of participants who are similar to your target
population.
 Pre-testing helps to identify any issues, such as confusing
wording, ambiguous questions, or technical problems, before
administering the survey to a larger sample.
 Pre-testing your questionnaire allows you to refine and
improve its clarity, comprehensibility, and overall quality
before launching the survey on larger scale.
 It helps to ensure that respondents will have a positive
experience and provide accurate and meaningful responses.

Cont…
# 9 Finalize the questionnaire
o Incorporate any changes or improvements based on the pilot
test.
o Review the questionnaire for clarity, consistency, and overall
quality.
o Ensure it is concise and be completed within a reasonable time
frame.

Cont…
 # 10 Distribute questionnaire
o Implement the chosen survey method to distribute the
questionnaire to the audience.
o This may involve sending online survey links, conducting
face-to-face interviews, or using other appropriate methods.

Cont…
#11 Analyze Responses
o One’s you have collected enough responses, analyze the data
using suitable statistical techniques or qualitative analysis
methods, depending on the nature of the data.
o Interpret the results in relation to your research objectives.

CONTINGENCY QUESTIONS
 Contingency questions are questions that are only asked to
respondents who meet certain criteria based on their
previous answers.
 They can help you improve your questionnaire by
avoiding irrelevant or confusing questions, reducing the
length and complexity of the survey, and collecting more
specific and accurate data.

CHAPTER FIVE
ANALYZING SURVEY DATA
 What is quantitative data analysis?
 Despite being a mouthful, quantitative data analysis
simply means analyzing data that is numbers-based – or
data that can be easily “converted” into numbers without
losing any meaning.
 For example, category-based variables like gender,
ethnicity, or native language could all be “converted” into
numbers without losing meaning. For example, English
could equal 1, French 2, etc.

 This contrasts against qualitative data analysis, where
the focus is on words, phrases and expressions that
can’t be reduced to numbers.
What is quantitative analysis used for?
 Quantitative analysis is generally used for three
purposes.
 Firstly, it’s used to measure differences between
groups. For example, the popularity of different clothing
color’s or brands.
 Secondly, it’s used to assess relationships between
variables.
 And third, it’s used to test hypotheses in a scientifically
rigorous way. For example, a hypothesis about the
impact of a certain vaccine.
 Again, this contrasts with qualitative analysis, which can

 How does quantitative analysis work?
 Well, since quantitative data analysis is all
about analyzing numbers, it’s no surprise that it
involves statistics.
 Statistical analysis methods form the engine that powers
quantitative analysis, and these methods can vary from
pretty basic calculations (for example, averages and
medians) to more sophisticated analyses (for example,
correlations and regressions).

The two “branches” of quantitative analysis
o Quantitative analysis is powered by statistical analysis methods.
o There are two main “branches” of statistical
methods that are use
descriptive statistics and inferential statistics.
o In your research, you might only use descriptive statistics,
or you might use a mix of both, depending on what you’re
trying to figure out.
o In other words, depending on your research
questions, aims and objectives.

1. DESCRIPTIVE STATISTICS
 Descriptive statistics serve a simple but critically
important role in your research –
to describe your data set.
 In other words, they help you understand the
details of your sample.
 Descriptive statistics are used to summarize and
describe the main features of a dataset.
 They provide a way to understand the central
tendency, variability, and distribution of the data.
 Descriptive statistics are all about the details of
your specific data set

Descriptive statistics…
 Descriptive statistics are numerical measures used to
summarize and describe the main characteristics of a
dataset.
 They provide a concise and meaningful summary of the
data, allowing for better understanding and interpretations.
 Descriptive statistics can be computed for both numerical
and categorical data.
 They provide a snapshot of the data, allowing for
comparisons, identifying outliers, and gaining insights into
the underlying patterns and characteristics of the dataset.

Cont…
 What kind of statistics are usually covered in this section?
 Some common statistical tests used in this branch include the
following:
 Mean – this is simply the mathematical average of a range of
numbers.
 Median – this is the midpoint in a range of numbers when the
numbers are arranged in numerical order. If the data set makes up an
odd number, then the median is the number right in the middle of
the set. If the data set makes up an even number, then the median is
the midpoint between the two middle numbers.
 Mode – this is simply the most commonly occurring number in the
data set.
 Standard deviation – this metric indicates how dispersed a range of
numbers is. In other words, how close all the numbers are to the
mean (the average).

What is Central Tendency?
 Measures of central tendency are summary statistics that
represent the center point or typical value of a dataset.
 Examples of these measures include the mean, median,
and mode.
 These statistics indicate where most values in a distribution fall
and are also referred to as the central location of a distribution.
 You can think of central tendency as the propensity for data
points to cluster around a middle value.

 What kind of statistics are usually covered in this
section?
 Some common statistical tests used in this branch include the
following:
 Mean – this is simply the mathematical average of a range of
numbers.
 Median – this is the midpoint in a range of numbers when the
numbers are arranged in numerical order. If the data set
makes up an odd number, then the median is the number
right in the middle of the set. If the data set makes up an even
number, then the median is the midpoint between the two
middle numbers.
 Mode – this is simply the most commonly occurring number in
the data set.

1. Mean in statistical analysis
 Mean is the average of given numbers and is calculated
by dividing the sum of given numbers by the total
number of members.
 In statistics, the mean is one of the measures of central
tendency, apart from the mode and median.
 Mean is nothing but the average of the given set of
value.
 To calculate the mean, we need to add the total values
given in a datasheet and divide the sum of data number
by the total number of values.

3, 3, 6, 9, 16, 16, 16, 27, 27, 37, 48
Added together, you get 208.
Divide 208 by 11 (the number of
data points) to get the mean,
which is 18.9.

2. Median in statistical analysis
 The median is the value in the middle of a data set, meaning
that 50% of data points have a value smaller or equal to the
median and 50% of data points have a value higher or equal
to the median.
 The term median refers to a metric used in statistics.
 It is the middle number in a sorted ascending or descending
list of numbers and can be more descriptive of that data set
than the average.
 It is the point above and below which half (50%) of the
observed data falls, and so represents the midpoint of the
data.
 The median is the middle number in a sorted list of numbers
and can be more descriptive of that data set than the average.

How to calculate the median?
3, 3, 6, 9, 16, 16, 16, 27, 27, 37,
48
 The median is 16, the data point in the exact
middle of the set.
 This set has an odd number of data points, which
makes it easier to find the middle. For a set with
an even number of data points, you'd take the
mean of the two middle numbers to find the
median.

3. Mode
 The mode is the value that appears most frequently in a data
set.
 In statistics, the mode is the most commonly observed value in
a set of data.
 For the normal distribution, the mode is also the same value as
the mean and median.

What Is Mode in Statistics With an Example?
 The mode in statistics refers to a number in a set of
numbers that appears the most often.
 For example, if a set of numbers contained the following
digits, 1, 1, 3, 5, 6, 6, 7, 7, 7, 8, the mode would be
7, as it appears the most out of all the numbers in the set.

Standard deviation
 It is the square root of variance.
 It involves a measure of the average distance between
each of value and mean.

SD = √Σ(xi− ¯x)2/n−1
Variance:
• The average of the squared difference between each
value and the mean.
• It measures the spread of the data

2. Inferential statistics
 Inferential statistics is a branch of statistics that
involves drawing conclusions or making inferences
about a population based on data collected from a
sample.
 It allows us to generalize the findings from a sample
to the larger population from which the sample was
taken.
 Inferential statistics plays a crucial role in scientific
research, decision making, and understanding the
characteristics of populations based on limited
sample data.
 It helps researchers make generalizations and draw
meaningful conclusions from their data.

Inferential statistics…
The process of inferential statistics typically
involves the following step;
A) Formulating hypothesis: the first step is to state a
hypothesis about the population parameter(s) of interest.
 The hypothesis can be a null hypothesis, which
assumes no difference or relationship, or/and alternative
hypothesis, which suggests a difference or relationship
exist.
B) collecting data: data is collected from a representative
sample of the population.
 The sample should be selected using appropriate
sampling methods to ensure it is representative and
avoids bias.

Inferential statistics…
C) Analyzing the data: the collected data is analyzed
using statistical techniques, such as hypothesis testing
or estimation.
These techniques help determine the likelihood of
observing the sample results if the null hypothesis
were true.
D) Drawing conclusion: based on the analysis,
conclusions are drawn regarding the hypothesis.
 These results may lead to accepting or rejecting the
null hypothesis, or providing estimates and
confidence intervals for population parameters.

Common inferential statistical methods includes:
 Hypothesis testing: this involves comparing data to the null
hypothesis and determining whether there is enough evidence
to reject the null hypothesis in favor of the alternative
hypothesis.
 Confidence intervals: confidence intervals provide a range of
plausible values for a population parameter, based on the
sample data.
 Regression analysis: regression analysis examines the
relationship between variable and allows for prediction and
inference about the relationship in the population.
 Analysis of variance (ANOVA): ANOVA is used to compare
means across multiple groups to determine if there are
significant differences between them.

CHAPTER SIX
RESEARCH REPORT WRITING

Introduction
 The main reasons for carrying out research is to add to the
existing body of knowledge.
 Hence, when conducting research, you need to document your
processes and findings in a research report.
 Along with a research report, it is easy to outline the findings
of your arranged investigation and any gaps needing further
inquiry.
 Knowing how to create a detailed research report will justify
useful when you need to conduct research.

Cont…
 Research is the systematic investigations into study of a
natural phenomena or materials or sources or existing
condition of the society in order to identify facts or to get
additional information and derive new conclusions.
 It is a production process, which needs a number of inputs to
produce new knowledge and application of new and existing
knowledge to generate technology that ultimately may
generate economic prosperity of a nation.

Research report
 A research report is a systematic write up on the findings of
the study including methodologies, discussion, conclusions
etc.
 A research report is a well-crafted document which outlines
the processes, data, and findings of a planned investigation.
 It is an important document that serves as a first-hand account
of the research process, and it is typically considered as an
objective and accurate source of information.
 To some degree, a research report can be considered as a
conclusion of the research process that understandably
highlights findings, recommendations, and other important
details.
 Reading a well-written research report should provide you
with all the information you need about the core areas of the
research process.

Characteristics of a Research Report
1. It is a detailed presentation of research processes and findings,
and it usually includes tables and graphs.
2. It is written in a formal language.
3. It is informative and based on first-hand verifiable
information.
4. It is formally structured with headings, sections, and bullet
points.
5. It always includes recommendations for future actions.

How to improve research writing
 Improving research writing requires a combination of
knowledge, skills, and practice.
 Here are some tips to enhance a researcher writing
abilities.
 Understanding the purpose: clearly define the
purpose and objectives of the research. This will help
you maintain focus and structure your writing
accordingly.
 Plan and organize: develop a well-structured outline
before you start writing. This will help you organize
thoughts, identify main section of your paper, and
ensure a logical flow of ideas.
 Conduct thorough research: gather relevant and

Cont…
 Analyze information: carefully analyze the
information you gather and synthesize it into coherent
arguments. Identify key themes, patterns, and
connections within your research to present a
comprehensive overview of the topic.
 Develop a strong thesis statement: Craft a clear
and concise thesis statement that encapsulates the
main argument or purpose of your research. Ensure
that your thesis statement is specific, focused, and
capable of being supported by evidences.
 Use clear and concise language: write in a clear,
concise, and straightforward manner. Avoid Jargon,
unnecessary technical terms, and convoluted
sentence structures.

Cont…
 Edit and proof read: revise your writing for clarity,
coherence, and grammar. Check for spelling errors,
punctuation mistakes, and grammatical inconsistencies. Read
your work aloud or ask someone else to review it for you to
catch any overlooked errors.
Improving research writing is an ongoing process.
Continuously seek opportunities to learn, practice, and refine
your skills to become a more effective and confident research
writer.

Contents of Research report
 Title
 Acknowledgement
 Abstract
 Introduction
 Research problem, questions
 Research objectives
 Literature review
 Research methodology: Research approach, design, methods, sample
design and sample size
 Results or finding/Discussion
 Conclusion and recommendations
 References
 Appendices, where applicable

Title
 The title summarizes the main idea or ideas of your
study.
 A good title contains the fewest possible words that
adequately describe the contents and/or purpose of your
research paper.
 The title is without doubt the part of a paper that is read
the most, and it is usually read first.

Acknowledgement
 The acknowledgements section is your opportunity to
thank those who have helped and supported you
personally and professionally during your thesis or
dissertation process.
 Senior-essay, thesis or dissertation acknowledgements
appear between your title page and abstract and should
be no longer than one page.

ABSTRACT
 An abstract is a brief summary of a research article,
thesis, review,, or any in-depth analysis of a particular
subject and is often used to help the reader quickly
ascertain the paper's purpose.

Introduction/Background of the staudy
 The introduction to a research paper is where you set
up your topic and approach for the reader.
It has several key goals:
 Present your topic and get the reader interested.
 Provide background or summarize existing research.
 Position your own approach.
 Detail your specific research problem and problem
statement
 Give an overview of the paper’s structure.
 The introduction looks slightly different depending on
whether your paper presents the results of original
empirical research or constructs an argument by
engaging with a variety of sources.

Statement of the Research
 A research problem statement is a clear, concise, and specific statement that
describes the issue or problem that the research project addresses.
 It should be written in a way that is easily understandable to both experts and
non-experts in the field.
 To write a research problem statement, you should:
 Identify the general area of interest: Start by identifying the general area of
research that interests you.
 Define the specific problem: Narrow down the general area of interest to a
specific problem or issue.
 Explain the significance of the problem: Provide context for the problem by
explaining why it is important to study and what gap in current knowledge or
understanding it fills.
 Provide a clear and concise statement: State the problem in a clear and concise
manner, making sure to use language that is easily understood by your intended
audience.
 Use a scientific and objective tone: The problem statement should be written in
a neutral and objective tone, avoiding any subjective language and persona bias.

Research objectives
 Objectives can help you stay focused and steer your research
in the required direction.
 They help define and limit the scope of your research, which
is important to efficiently manage your resources and time.
 The objectives help to create and maintain the overall
structure, and specify two main things—the variables and the
methods of quantifying the variables.
A good research objective:
 Defines the scope of the study
 Gives direction to the research
 Helps maintain focus and avoid diversions from the topic
 Minimizes wastage of resources like time, money, and energy

Literature review
 A literature review surveys prior research published in
books, scholarly articles, and any other sources relevant to a
particular issue, area of research, or theory, and by so doing,
provides a description, summary, and critical evaluation of
these works in relation to the research problem being
investigated.
 Literature reviews are designed to provide an overview of
sources you have used in researching a particular topic and
to demonstrate to your readers how your research fits within
existing scholarship about the topic.

 A literature review may consist of simply a summary of key sources,
but in the social sciences, a literature review usually has an
organizational pattern and combines both summary and synthesis,
often within specific conceptual categories.
 A summary is a recap of the important information of the source, but
a synthesis is a re-organization, or a reshuffling, of that information
in a way that informs how you are planning to investigate a research
problem.
 The analytical features of a literature review might:
 Give a new interpretation of old material or combine new with old
interpretations,
 Trace the intellectual progression of the field, including major
debates,
 Depending on the situation, evaluate the sources and advise the
reader on the most pertinent or relevant research, or
 Usually in the conclusion of a literature review, identify where gaps
exist in how a problem has been researched to date.

Research methodology: Research approach, design, methods,
sample design and sample size
 Research methodology is the path through which researchers need
to conduct their research.
 It shows the path through which these researchers formulate their
problem and objective and present their result from the data
obtained during the study period.
 This research design and methodology chapter also shows how the
research outcome at the end will be obtained in line with meeting
the objective of the study. This chapter hence discusses the research
methods that were used during the research process.
 It includes the research methodology of the study from the research
strategy to the result dissemination.

Cont…
 For emphasis, in this chapter, the researcher outlines the
research strategy, research design, research methodology,
the study area, data sources such as primary data sources
and secondary data, population consideration and sample
size determination such as questionnaires sample size
determination and workplace site exposure measurement
sample determination, data collection methods like
primary data collection methods including workplace site
observation data collection and data collection through
desk review, and secondary data collection methods, etc.

Research findings /results or
discussion
 The results section of your research paper contains
a description about the main findings of your
research, whereas the discussion section interprets
the results for readers and provides the significance
of the findings.
 The discussion should not repeat the results.

Cont…
 The discussion section is one of the final parts of a research
paper, in which an author describes, analyzes, and interprets
their findings.
 They explain the significance of those results and tie
everything back to the research question(s).

Cont…
 The discussion reviews the findings and puts them into the
context of the overall research.
 It brings together all the sections that came before it and allows
a reader to see the connections between each part of the
research paper.
 In a discussion section, the author engages in three necessary
steps: interpretation, analysis, and explanation.
 An effective discussion section will tell a reader why the
research results are important and where they fit in the current
literature, while also being self-critical and candid about the
shortcomings of the study.

Summary/Conclusion
 This section is concerns with the report of the findings in relation to
all the research questions (or research hypothesis) investigated in
the study.
 They are to be listed in the order they were stated in chapter one
and the conclusion reached in relation to each would be stated.
 The purpose of this section is to show the reader what the study
found before the researcher discusses the implications of the results.
 It is now time to go through each section and highlight the critical
statements.
 What information does the reader have to fully comprehend the
article’s central argument or inference?
 Remember that a summary does not necessitate rephrasing every
single line of the article.

Cont…
 The conclusion section of a research paper focuses on
discussing the essential features and the significant outcomes
of your research.
 It highlights to your readers the importance of your research to
them after they have read through it.
 The conclusion should be written in relation to the
introduction in your research paper.
 This means that your conclusion should be written in such a
way that it relates to the aims of the research paper.

References
 A reference is a detailed description of the source of
information that you want to give credit to via a citation.
 The references in research papers are usually in the form of a
list at the end of the paper.
 The essential difference between citations and references is
that citations lead a reader to the source of information,
while references provide the reader with detailed
information regarding that particular source.

Appendixes
 The appendix is a section that is placed at the end of the
thesis and may contain material such as tables, figures, maps,
photographs, raw data, computer programs, musical examples,
interview questions, sample questionnaires, CDs, and many
other types of material.

Quantitative research methodology and survey design

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