Download Experience

Business Research
Methods (CURMCS223)
Introduction
The need to do research or an Inquiry is varied.
But the main ones include:
a) Adding to knowledge
b) Evaluation of existing knowledge and explain
further
c) Answer Questions
d) Test theories or hypothesis
e) Find solutions to problems
Way of understanding the World
Phenomenon
We can understand how things work in three
ways:
• Experience
• Reasoning
• Research
_____________
continue
Experience
• Draw on individual accumulation of body of
knowledge and skills obtained through
contact with facts and events in your
environment.
• Consult those with experience (experts)
• Using experience you could come up with
hypothesis and questions about the real
world.
Continue
Reasoning:
Type of reasoning
1. Deductive reasoning
2. Inductive reasoning
3. Inductive – deductive reasoning
Deductive Reasoning
Deductive Reasoning
(Aristote)
This approach follows logic: For examples
• All human beings walk on two legs
• John is a human being
• Subsequently John walks on two legs.
Continue
• All plants revolve round the Sun and Earth
revolves round the Sun the earth is a planet.
• Thus, we move from general; logically to a
particular case.
• Valid conclusions are deduced from valid
premises.
Continue
The deductive reasoning lost its importance
because it was noticed that it was not related
to observation and experience. This makes it
more of a mental exercise. In the deductive
reasoning empirical evidence as a basis of
proof is superseded by authority or mental
reasoning only. This kind of reasoning had and
adverse effect on science.
Observation basis of science
• Francis Bacon (1600c) argued that deductive
reasoning was not objective, but promoted
preconceived ideas and these in turn biased
the conclusion.
Inductive Reasoning
• Francis Bacon proposed inductive reasoning
• This kind of reasoning leads to hypotheses
formation and generalization of individual
case.
• Collect data and confront it with theory, this
will maintain complete objectivity.
• The inductive reasoning demands empirical
evidence for verification.
Inductive – Deductive Reasoning
• The Inductive – Deductive approach led to:
1. The suggestion of hypotheses
2. The logical development of these hypotheses
3. The clarification and interpretation of
scientific findings and their synthesis into a
conceptual framework.
Research (discovery of Truth)
There are many definition as to what research is.
However, no definition is 100% correct. The
most important thing is to understand the
concept and apply it correctly.
Kerlinger, F.N. (2000) define research as” The
systematic, controlled, empirical and critical
investigation of hypothetical propositions
about the presumed relations among natural
phenomena”.
continue
• Others use the concept of research to refer to the
process of using scientific methods to expand
knowledge in a particular field of study.
• The research approach also employs inductive –
deductive approach.
• Research is self correcting
• Uses accepted scientific method
• Can be disapproved by other professions, i.e.
Findings. Incorrect results will be found out and
rejected or corrected.
continue
• Research is a combination of both experience
and reasoning and is the most successful
approach to the discovery of truth.
_________________
Assumptions: Social Reality (Burrel &
Morgan, 1979)
Assumption
1. Ontological Kind – Internal or external to an
individual
2. Epistemological kind – Concern basis of
knowledge its nature & form how it can be
acquired and how communicated to other
human beings. Epistemological assumption –
tell us which knowledge can be acquired or
obtained through experience.
continue
• Knowledge of social behaviour – is either hard
or soft – If hard –need observation (natural
science). If soft –subjective and cannot follow
natural science.
• If knowledge is hard it is referred to as
positivist and follow natural science. Soft
knowledge is referred to as anti-positivist.
Continue
3. Concern Human nature (assumption): The
relationship between human beings and their
environment. Human beings are both subject
and object of study (social science).
• Human beings respond mechanically to
environment
• Human beings are initiators of their own
actions.
continue
• Are human beings controllers of environment
or controlled by environment.
• Determinism Voluntarism (extremes)
Most social scientist-take the middle road.
These three assumptions lead to choice of
methodology.
continue
4. Methodology – All the previous assumptions
have implications for methodology or
methodological concerns of the researcher.
Researchers (hard-objective) followexperiments, surveys, positivist approach.
(soft-subjective) follow- anti-positivist approach.
continue
Stages of searching for the truth:
1. Theological stage (primitive to explain behaviour
in terms of spiritual or supernatural
terms/entities
2.Metalphysical stage
(modification of uses abstractions or
forces/depersonalize beings of earlier theology
3. Positive stage (observation and
reasoning as a means of understanding
behaviour. Scientific description, observation and
experiments.
continue
• “The central belief of the logical positivists is
that the meaning of a statement is, or is given
by, the method of verification – It follows from
this that unverifiable statements are held to
be meaningless, the utterances of traditional
metaphysics and theology being included this
class”
continue
• Methodological procedures of natural science
may be directly applied to the social sciences –
positivism here implies a particular stance
concerning the social scientist as an observer of
social reality.
• End results of social scientist can be interpreted
just like that of natural science.
• Positivism-involves a definite view of the social
scientist as analyst or interpreter of his subject
matter.
Features of Positivism - Method
“Assumptions and Nature of Science”
1. Determinism – Events have causes (this link can
be studied – event determined by other
circumstances) a law should be there because of
universe has order, follow them & you will be
able to predict & control.
2. Empiricism – That which is variable by
observation; and evidence, data yielding proof
or strong confirmation in probability terms of a
theory or hypothesis in a research setting.
Five steps in the process of empirical
science
a) Experience – starting point of scientific
elementary level
b) Classification – Data arrangement
c) Quantification – analysis using mathematical
means
d) Discovery of relationships among phenomenon
e) Approximation to the truth – science proceeds
by gradual approximation to the truth.
What is Science
Static & dynamic view of science:
Static – science is an activity that contributes
systematised information to the world.
Scientist discover new knowledge and add to
existing knowledge. Science is thus seen as an
accumulation of body of findings, the emphasis
being chiefly on the present state of knowledge
and adding to it. Dynamic view – takes the above
plus discovery that scientist make.
continue
• Model implies Theory: Used interchangeably
both are seen as explanatory devices or
schemes having a broadly conceptual
framework. Theory is provisional – does not
cover everything – can be modified.
The Tools of Science
• Concepts and the hypothesis:
1. Concepts: Express generalisation from
particulars e.g. Democracy, achievement, etc.
Each one is a word representing an idea or
concept. Concepts give meaning to the real
world. Your ability to think and comprehend
the world we live in depends on the command
of concepts.
Continue
2. Hypothesis – cause and effect or educated
guess. If you have a problem form a
hypothesis.
Hypotheses & concepts play a crucial part in the
scientific method.
continue
3. Principle of parsimony – Explain in the
economic way. Simple theory is to be
preferred to a complex one.
4. Generality – start with observation of
particular, the scientist generalize his findings
to world at large.
The Scientific Method
• A scientific approach involves
standards and procedures for
demonstrating the empirical
way and its findings. Standards
and procedures are methods.
The Research Process and Procedure
(Start of the process)
1. Definition of concepts method and
methodology.
• A method is an instrument, tactic, for
collecting data, solving problems and arriving
at new knowledge information.
• Methodology is a strategy: a term often very
loosely used in business to describe the way
in which professions proceed in their analysis
of a problem.
2. Research Process continue
To follow a certain acceptable research process
is important for your findings to be acceptable
or valid. Accepted procedures should be
followed, for example:
1. The formulation of the problem of study and
deciding on the focus.
Continue
• Before you start doing your research work,
you need to be clear on:
Subject matter, background information
What is it that you would like to do i.e. Focus.
• State the problem clearly. A clear and precise
formulation of the problem will assist you in
later phases of the investigation.
Continue
• Degree of clarity in formulating a problem
depends on:
i. Complexity of the problem
ii. Amount of information already known about
the problem.
Continue
2. Choice of Units and variables to be analyzed
and confronted with data.
a. Unit of Analysis
b. Variable of analysis
Example:
Problem of analysis “Income distribution among
workers in the agricultural sector.
Continue
• We are interested in “workers in the
agricultural sector”. Hence object of
investigation is “workers in the agricultural
sector” is the Unit of analysis.
• ‘Income distribution’ is the particular
characteristic that we are interested in. Hence:
the variable of our analysis.
• Workers (Fixed). Income received- variable.
Continue
• The focal point of the study is always the unit
of analysis.
3. Objective(s) or aim(s) of the study.
Having stated the problem – the objectives of
your research should be clearly stated, should
be achievable and not too many.
continue
4. Significance of the study to the society
• Explain how your subject is useful or why it is
important that this subject should be studied.
• Who has an interest in your research results
• What do we know already about the topic.
• How will this research add to practice, policy
and knowledge.
Continue
5. Research Questions, Hypothesis
Hypothesis statement:
Hypothesis is a statement indicating a
relationship or its absence, between two or
more of the chosen variables and stated in a
way as to carry clear implication for testing.
There are two types of hypotheses : a) Null
hypothesis and Alternate. Null implies no
relationship and this is what you are testing.
continue
Some ideas on the formulation of questions or
hypothesis:
(1) It is important to choose an area that you
know or are familiar with.
(2) Widen your experience (reading widely on
your chosen subject to start with.
For example: If you are interested in agricultural
finance of small farmers, also read about the
large commercial farmers.
continue
• This will help in improving your
questions/hypotheses.
(3) Brainstorm – to start with (i.e. How your
questions or hypothesis should be stated)
(4) Do not allow a method/technique to lead
you into deciding on your
question(s)/hypotheses.
Continue
5. The hypotheses should assist in choosing of
an appropriate research strategy and method
for your research.
6. Put emphasis on the statistical hypotheses,
the Null form
7. Whatever, hypothesis you formulate, should
be testable statistically. So be sure about the
form of causality, positive or negative
relationship of variables.
Continue
8. Hypothesis should be brief and clear as to
what is it to be tasted.
Continue
9. Your hypothesis should clearly state
the relationship between two or
more variables that you intend to
analyse.
10. You should have a reason based on
general theory, why the hypothesis
should be tested.
Continue
11. On the basis of the research findings or
evidence, the hypothesis is accepted or
rejected, then link it with original problem
objectives and questions.
12. Literature review , theory/previous studies.
_______________
Methodology (what strategy) and
methods of data collection
• Research strategy refers to the general
approach that you choose for your research.
• The traditional strategies used in collection of
data include:
1. Case study
2. Survey
3. Experiments
Characteristics of a case study
• All case studies involve undertaking some
applied Analysis
• Most case studies involve fieldwork
• In most cases the material from a case study is
original
Characteristics of a Survey
• Surveys involve selection of samples and
collection of data from a defined or known
population. The format in surveys is standard.
• Surveys obtain data at a given point in time
(cross-section), and the reasons for collecting
data, vary, depending on the requirements of
the investigation.
Characteristics of Experiments
The main features of experimental research
strategy is that the researcher/or investigators
changes or controls one variable and then
observe the effect of the changes or controls
one variable and then observe the effect of
the changes on another variable of interest.
Continue
• Example, take a sample from a known
population and carry out the experiment by
controlling certain variables and observe the
reaction on the chosen sample.
Given a function: Y = Y(x); a change in value of
‘x’ and observe the effects of the change in
value of ‘Y’.
Continue
Call ‘x’ independent variable and ‘Y’ the
dependent variable.
Response
stimulus
Dependent variable
Independent
variable
At this stage of the research process mention
the (instrument(s) to be used to collect data.
Collection of data
Data is collected from a known population
a) ‘Censuses survey’ collect population data
b) ‘Sample survey’ collect sample data
The data is of two types the secondary data
which is already collected and documented
and the primary data, which is a new data
that the investigator collects
continue
• Recall the generality assumption, from the
sample survey we generalise to the population
from which the sample is drawn.
____________________
Types of data
• Qualitative type: This kind of data or
information is non-numerical. It assist the
researcher in explaining the numerical data
• Quantitative data: This kind of data is in
numerical form and can be used in statistical
analysis.
Data Processing
The data collected need to be processed. There
are many ways of processing data such as:
Classification of observations
Coding of observations – coding is the process
of assigning code values E.G. 385 -9, 311 to
the various alternative answers to survey
questions either when constructing the
questionnaire (pre-coding) or after data
collection (post-coding).
Discussion Issues
• Are assumptions necessary in Research?
Discuss.
• Discuss the significance of all steps in a
research process.
Data Processing
The data collected need to be processed. There
are many ways of processing data, these
include:
Classification of observations through;
• Coding of observations
For example:
If female adult 02
If male adult
01
Continue
If female child 03
If male child
04
This is the kind of coding that can assist in
classification of data. Coding is usually done at
the questionnaire or interview level.
Continue
The researcher after fieldwork make notes or
rearranges the data in a way that will be easy
to analyse. The investigator may need to
expand on the information collected, for
example, data tape recorded need to be
processed.
Analysis of data
The process of data analysis entail three
activities:
• Data reduction (coding, etc)
• Data display, i.e., display data in graphic
formats such as matrices, charts, figures,
graphs and tables.
• Conclusion drawing/ verification
Dealing with data
•
•
•
•
Scatter diagrams
Correlation Analysis
Regression Analysis (linear relationships)
Other statistical tests of hypotheses.
Data Interpretation
This stage of research process can be combined
with data analysis. Data interpretation links
the real world phenomena with the theory. It
brings out the significance of the data
Statistical methods such as regression analysis
using correlation are used.
Continue
Regression analysis and significance of the
relationship, should be supported (backed) by
relationship derived from tables, simple twoway graphs. This will show if relationships are
consistent with the theory.
Writing of Research Report
A good well presented report will be acceptable
to examiners than a poorly presented one, but
with good material.
• Use of your report:
1) A project/ dissertation can be submitted for
you degree
2) Part of it can be sent to professional journal
3) You could produce a book
Continue
4) Any other group that might be interested in
your work could ask you to present or publish
your work
_____
Some of the things to note in your final report.
In your final report mention the problems
experienced and the possible causes.
Continue
• Review other surveys or finished and
published reports
• The report should state the objectives of the
project and the whole research process
leading to the final conclusion
• Indicate your contribution to the subject or
discipline. What is the importance of your
results to the policy maker.
Conclusion (end of research process)
The conclusion sums up the research work
touches on the main points and make the final
statement about your research. It makes the
reader to understand the purpose of the
research. The conclusion should be brief and
to the point.
Historical Research
Historical research deals with ex post
information. Literature review in a scientific
research could be viewed as historical.
Cohen & Manion (1990) define historical
research as the systematic, and objective
location, evaluation of evidence in order to
establish facts and draw conclusions about
past events.
Continue
• In business and industrial sectors it is,
perhaps, important to understand, the
industrial history of a people. How did the
present industrial set up come about.
Historical research brings benefit to the sector
and assist in solving some problems of
historical nature. Helps in understanding
between, for example, politics and industrial
production or for example, the lack of factor
of production such as capital.
Development Research
• Development research deals with descriptive
research as opposed to experimental
research. Descriptive research deals with what
has occurred, while experimental research
make things to happen. Most of the research
and investigation in business and economics
describes what has already happened.
Continue
• The objective being to examine behaviour and
choice of individuals, groups and institutions.
In doing so the researcher describes contrast,
classifies, analyses and interpret the events.
Three Types of Descriptive Research
1)
2)
3)
4)
Longitudinal
Cross – Sectional
Trend or prediction
The three types of research described
present relationships among variables and
changes in relationships overtime.
Terminology of Developmental
Research
Longitudinal – describe studies done overtime
and deal with human development.
Example: From development economics
a. Traditional
b. Transitional
c. Take – off
d. Maturity
e. High Mass Consumption
continue
Another example: In marketing – Product life
Cycle: Sales over Time
a) Development stage
b) Introduction stage
c) Growth stage
d) Maturity stage
e) Decline stage
Continue
In agriculture: Agricultural Development
1. Traditional
2. Feudal
3. Commercial
Cross - Sectional
Different respondents are studied at the same
time. There could be a series of these cross –
sectional studies if the researcher wishes to
compare. A cross –sectional study produces a
Snapshot of a population at a chosen time, for
example, national census of a group of
enterprises.
Trend Study
Where selected factors are studied continuously,
i.e., weekly, monthly or yearly, the term trend
study is often used.
________
SURVEYS
Surveys gather cross – sectional data, i.e. Data is
obtained at a particular point in time with a
view of:
a) Describing the nature of existing conditions
b) Identifying standards against which existing
conditions can be compared.
c) Determining the relationships that exist
between specific events
Continue
Large – scale or small – scale surveys all use
similar data collection techniques. For
example, structured or semi – structured
interviews, self – completing or postal
questionnaires. There are no limits to cases
covered by surveys.
Survey Preliminary studies (Plan)
The planning of survey is a combination of
technical and organizational decision.
Questions to ask
•
•
•
•
What population coverage to aim at?
What information to seek?
How to go about collecting this information?
How to process and interpret results?
Continue
Sample design (methodology) decided in the light
of:
• What is practically feasible
• What is theoretically desirable
• Accuracy of results
• Cost, time and labour involved
• Type of sampling
• Type of data collection
• Methods of tabulation
• Miscellaneous items
Preliminary plan of a survey
1. Statement on: Objective(s) or purpose of the
enquiry.
• Clear statement in detail
• Methods to be used
• Why the survey, what questions it will cover
or answer
• What results expected
• How the information will be used.
continue
2. Population
• Define population targeted
• Geographical, etc
• Covered fully or partially
• Method of selecting respondents
• Sample in a statistical sense
• Sample frame list
continue
Sample frame: A listing that should include all
those in the population to be sampled and
exclude all those who are not in the
population.
• How will you deal with non-response
• Follow up approach
Collection of Data
• The collection of data will depend on the size
of survey
Questionnaires
Plan how to structure and phrase your
questionnaires.
Errors
Every stage of survey can lead to errors or errors
are made.
Continue
For example:
• Sampling error
• Interviewing
• Questions
• Editing
• Coding
• Tabulation
Anticipate likely sources of error and size.
Fieldwork
• Central stage of survey and will depend on the
quality of interviews.
Processing & Analysis
• Questionnaire – check on : Omissions
• Statistical Calculation
• Editing scheme is necessary
• Tabulation plan
• Method of analysis
Continue
Timing & Cost
• Timing of investigation
• No holidays etc.
• When are the results needed
• Estimate Cost
Pre-test and Pilot Survey
• To find out the re-action of people to your
questionnaires or interviews
• Pilot survey – a small scale replica of the main
survey
Pilot Study Provides:
1) Adequacy of the sampling frame
2) Variability within the population to be
surveyed
3) Non-response rate to be expected
4) Suitability of data collection methods
5) Are the questions adequate: ease of
questions, layout, similarities, clarity, do the
answers meet your objectives.
continue
6) Are instruments clear
7) Codes – for pre- coded questions are they
clear to you.
8) Cost and time spent – and how well are you
organized in the field.
9) Approach to the respondents
10)After pilot – Improve on your plan.
Survey Sampling Design
Type of sample Design
Bias is one of the sampling problem that an
investigator may encounter.
• For a given sample design, the estimator is the
method of estimating the population
parameter from the sample.
Estimator: Is the sample arithmetic mean
Continue
• Example: E(b) hat
estimator of the
population parameter “ b”.
• Bias
• E(b) hat = b ; implies unbiased estimator of ‘b’
• E(b) hat
b; implies biased estimator of
‘b’
Continue
• For any sample design if the expected value of
the estimator is equal to the population
parameter then estimator is unbiased if not
equal to population parameter, it is biased.
• The difference between the expected value
and the true population value is termed the
bias.
Continue
• Bias = (‘b’ hat) – b
• Bias: The tendency for some extraneous
factors to affect the answers to survey
questions or the survey results in general, in a
systematic way, so that results are “pushed”
or “pulled” in some specific direction.
Decision Errors
• Generally the purpose of statistical inference
is to make an educated guess about what
exists in the population when only a small
subset of cases from the population has been
studied. Since the decision is a guess, it might
be wrong.
Continue
• Type 1 error occurs when a null hypothesis is
rejected when it is in fact true.
• Type 11 error occurs when the null hypothesis
is accepted when it is, in fact false.
• Given the validity of the null hypothesis, the
probability that it is erroneously rejected by
these procedures equals,
level.
α
, the significance
Causes of Bias
Three factor that might cause bias include:
1) Non – random method(s) used to select a
sample, in such cases there is a likelihood of
subjectivity.
2) Incomplete or inaccurate sampling Frame
from which a sample is selected.
3) Non – response of those included in the
sample –which mean the sample will not be
representative of the population.
Continue
• Bias through sampling method can be avoided
by using random method
• A good sampling design should use a random
method. Note that there are two main types
of sampling: random or probability sampling
and non-probability sampling.
Continue
• In general, a random or probability method of
choosing a sample is defined as that which
allow each of the members of the targeted
population a calculable probability of being
included in the sample.
Continue
a) Unrestricted Random Sampling: Give an
equal chance to every member of the
population of being selected. However, in
unrestricted random sampling the
investigator has to replace the members
selected. Hence, unrestricted random
sampling, is sampling with replacement. It is
therefore, likely that a member may be
selected more than once.
Simple Random Probability Sampling
• The simple random sampling is done without
replacement. Subsequently, no member can
be selected more than once in any given
sample. In a simple random probability
sampling each member of the population has
a chance of being included in the sample.
Continue
Examples of Simple Random Sampling
1) Tickets mixed in a basket pick one this
represent a simple random sampling.
2) Pick every nth member of the population,
this represents a simple random sampling
Methods of Ensuring Randomness in
Selection of Survey Samples
1) Lottery Method:
Number the population and represent
it with marked balls: 1 to n
Place the balls in a wheel or something
that mixes- then select required
sample.
Continue
2) Use random numbers (table):
Population numbered: 1 to Z; then sample
members are selected from the table in a
systematic fashion.
Continue
• In practice use random numbers:
Example. Handout (tables) Random table
Draw a sample of size 10 from 100 small scale
businesses.
Get a list of Business you want to investigate
Continue
1. Set the three digit numbers:
001, 002, 003, 004, .......010, 099-100
2. Go to Random tables
3. Along the column choose a number in digits
of three below 101 until you get your sample
4. Jump the repeat numbers.
SYSTEMATIC SAMPLING
Another method of sampling: Suppose you have
6000 small scale businesses and you want a
sample of 300
300/6000 = 1/20
1 – 20 pick any number at random between 1 –
20 and then every firm after 20th is picked.
• This is not a simple random sampling because
originally the 6000 were not randomly picked
and 1 – 20 is not randomly picked.
Continue
• The difference between the simple random
sampling and systematic sampling is that in
the systematic sampling the members are not
given equal chance of being included in the
sample. Once you pick the first number the
others are picked systematically or follow.
STRATISFIED RANDOM SAMPLING
In a stratified random sampling the population is
divided into groups or strata.
For example:
• Small scale firms (Businesses)
• Middle scale firms (Businesses)
• Large scale firms (Businesses)
The random sampling then take place
Continue
Within the stratum.
• Stratified random sampling with a uniform
sampling fraction tends to have greater
precision than simple random sampling.
Because of the small size of the stratum.
Proportionate stratified Sample Design
• In stratified sampling we do not require that
the sampling fraction be the same or uniform
for each stratum. But whenever the sampling
fraction is the same for each stratum, we refer
to this as a proportionate stratified sampling.
Cluster Sampling
The cluster Sampling is ideal when the
population is large and widely dispersed. The
researcher avoids long distance and at the
same time affords adequate information in
order to generalize to the rest on the
population.
In a cluster sampling the population is divided
into cluster or groups. The cluster units are
chosen at a random.
Continue
Multi-Stage Sampling
• the use of multi-stage cuts down on cost.
• Studies of very large population, such as a
whole country, usually involve multi-stage
sampling. Multi-stage sampling are an
extension of cluster sampling. The samples are
selected in stages. It implies taking samples
from samples. The sampling is done at
random.
Continue
Example 1.
Stage 1 10 Industrial Areas
Stage 2
100 Firms from the areas
Stage 3
10 specific Firms
Example 2.
Provinces ͢ Districts ͢ villages or towns ͢
individuals
Continue
Example 3.
No of Schools ͢ No of classes ͢
No of pupils
Non-Probability Sampling
Non-probability sampling it is frequently used in
practice in spite of its limitations.
• Convenience and lower costs per case are its
chief advantages
• Common statistical techniques which assume
a random sample should not be used in nonprobability samples
Continue
The main types of non-probability sampling are:
1. Convenience or Accidental, 2. Quota, 3.
Purposive, 4. Dimensional, 5. Snow ball
sampling
Convenience Sampling
This kind of sampling chooses individuals who
are near and these then constitute the
respondents. For example, firms near to the
researcher can be chosen and form the
required sample.
Quota Sampling
It is similar to stratified sampling. But in Quota
sampling respondents are not randomly
chosen. In a Quota sampling, a population is
divided into a Quota which in the case of firms
it could be small-scale and large –scale firms a
quota for each group could then be chosen
Purposive Sampling
The researcher picks the respondents to be
included in the sample, using his/her
judgement as to which respondents to be
included.
Dimensional Sampling
This is an extension of Quota sampling it
involves studying the population and knowing
the composition of the population. The
researcher then includes in the sample all
factors of the population. Within a group you
might want to know certain attributes and
attitudes. It is the differences within the
group.
Snowball Sampling
The researcher knows the characteristics
required. On a small group the researcher
then use this group as a representative and to
help the researcher to get or identify others to
be included in the sample, in turn, these
people lead the researcher to others, until the
required sample is obtained.
Tutorial Question
• Discuss the advantages and disadvantages of
random probability sampling and nonprobability sampling for each sampling
method discussed in class.
CASE STUDY
Case studies are based on observation of the
characteristics of the phenomenon or individual
unit to be studied or researched. For example, a
firm, a specific project, a community. These cases
are not chosen through a formal sampling
process, but by judgemental and a typical
relevant case is chosen. The aim of a case study is
to do an in-depth analysis of the unit. From the
study of the unit generalization is established for
the population from which the unit is drawn.
Types of observation: case study
• Participant observation: In a participant
observation the researcher (observer) takes
part in the activity required to be observed.
• For example, join the business for one year or
work in a project that you wish to study. Join
the community or firm in order to get an
insight of the organization.
Continue
• Although observation is the main
methodological strategy, various research
instruments or methods of collecting
information or data are used, depending on
whichever is appropriate, for example;
interviews, questionnaires.
TUTORIAL WORK
1. A researcher (enumerator) used a single
questionnaire for both smallholder farmers in
an estimation of agricultural production.
Comment on the use of the instrument in the
exercise.
2. Discuss the significance of inductive and
deductive reasoning in the development of a
scientific research method?
continue
3. Briefly mention and discuss three kinds of
bias related to sampling design.
4. Explain in detail giving examples the
assumption of Epistemology and
methodology in the nature for social sciences.