What is a Research Proposal? What purposes do a research proposal serve? Techniques of preparing a Research Proposal? What is “Inductive Reasoning” ? What is “Deducting Reasoning” ? What is sampling? What are the basis of sampling? Distinguish between random sampling and non-random sampling?

1. Business Research Methodology
Professor. M. Mokarrom
Hossain
Professor,
Faculty of Business & Economics
Daffodil International
University
Abdullah Al Maruf – 113 – 11- 2295

2. What is a Research Proposal?
Research Proposal is a written statement of the research
design. It is actually a blue-print for the future activities
of a research project. A research Proposal represents
the designing stage of a research project. It is a work-
frame for completing in the research.

3. What purposes do a research proposal serve?
A research proposal serves with the idea of researcher about –
What the wants to do.
What objectives and methodology he has set for the
researcher.
How much time and resources will be required to complete
it.
How the research findings would be reported and so on.

4. Point out the Techniques of preparing a
Research Proposal?
Planning of Research Proposal/ Techniques of Preparing a
Research Proposal :-
 Tittle:- Contribution and impact of RMG sector in Bangladesh
economy.
(The title should reflect the main theme of a research
work. It should be self-explanatory, should be as brief as
possible. Language should be simple. It should indicate
the overall contents of research findings.)

5. Introduction
Statement of the problem
Objective of the problem
a) Main objective/Broad
objective
b) Specific objective
Formulation of hypothesis
Review of related
literature (Some previous
research work or that field)
Justification of the
study/Rational of the study
Scope of the study
Working definition of the
concepts, assumptions,
limitations and delimitation
Research designing and
methodology
a) Population/Universe of the
study
i. Census i.e. that is
individual unite
ii. Sample i.e. that is sample
size, method of sampling
b) Sources of data
i. Primary source
ii. Secondary source

6.  Theoretical and conceptual
framework (The theoretical
frame work is the foundation on
which the entire research project
is based)
 Techniques/Methods of data
collection
a) By mailing Questionnaire
Through personal &
telephone Interview
b) By observation
c) Through schedule
d) Projective Technique
e) Document study
 Reliability and validity of
data
 Processing of data
a) Editing of the questionnaire
and schedule
b) Coding
c) Classification of data
d) Tabulation
e) Statistical test of significance

7.  Analysis of data
a) Descriptive Analysis
b) Inferential Analysis/ Statistical
Analysis
c) Correlation Analysis
d) Causal Analysis / Regression
Analysis
e) Chi-square Test ( )
 Time Reference ( Period for
which data are collected )
 Time schedule/Time budget
(Time required for the completion
of the research project )
 Money Budget
 Personnel, Researcher,
Enumerator, supervisor,
statistician
 Chapter Outline of the
proposed study
 Major findings of the study
 Summary, Conclusions and
Recommendations

8.  Bibliography
a) Questionnaire
b) Articles
c) Journal
d) Dissertation
e) Ph. D. Thesis
 Appendices/Appendix
Researcher Name:
Address:
Supervisor Name :
Address:

9. What is “Inductive Reasoning” ? Give Example
Inductive reasoning is the reasoning from particular facts to
a general conclusion, whereby observations and data are
collected with the assumption that relationship will become
apparent.
Example:
1. A drops of blood from any part of the body will indicate
the group of blood.
2. A house wife boiling rice tests only two or three grains and
tasks decision as to the whole rice is boiled or not.

10. What is “Deducting Reasoning” ? Give Example
Deductive reasoning is a process whereby through a series
of local steps conclusions can be reached based on valid
premises.
Example: The car does not start, to start the car you may
hypothesize
Several possibilities:
1. There is no gasoline in the tank.
2. The spark plus are workout.
3. Moisture has condensed in the distributor cap.

11. Define independent variable. Distinguish between
Moderating variable and intervening variable with example
and diagram.
Moderating variable
The variable which
directly influences both
the independent
variable and
dependent variable is
called moderating
variable.
Intervening variable
The variable which
directly influences the
independent variable
to make effecting of
the dependent variable
its called intervening
variable.
An independent variable is one that influences the
dependent variable and accounts for or explains the
variance in the dependent variable.

12. Moderating Variable
Suppose you are studying job
applications to various departments
within a large organization. You believe
that in overall, women applicants are
more likely to get the job than men
applicants, but that this varies by the
number of women already in the
department the person applied to.
Specifically, departments that already
have a lot of women will favor female
applicants, while departments with few
women will favor male applicants. We
can diagram this as follows
Intervening Variable
We said that diversity is good for
profitability because diversity
leads to innovation (fresh looks)
which in turn leads to profitability.
Here, innovation is an intervening
variable. We diagram it this way

13. What is sampling?
Sampling is a method
obtaining data or
information about the
population/ universe by
investigation only a
representative portion of
them. For example, a
housewife while boiling
rice tests only two or three
grains, and takes decision
as to whether the whole
rice is boiled or not.
What are the basis of
sampling?
1.Homogeneity of population.
2.Representativeness of the
sampling.
3.Level of accuracy of
prediction.

14. Distinguish between random sampling
and non-random sampling
Random Sampling
Probability sampling is also
known as ”random
sampling” or “ chance
sampling”. Under this
sampling design, every item
of the universe has an
equal chance of inclusion
in the sample. It is, so to say,
"lottery method” in which
individual units are picked
up from the whole group(
not deliberation) but by
some mechanical process.
The implications of random
sampling are-
 It gives each element in the
population an equal probability
of getting into the sample, and
all choices are independent of
one another.
 It gives each possible sample
combination an equal
probability of being chosen.
Random sampling is considered as
the best technique of selecting a
“representative sample”.

15. Probability sampling are of
following types:
1. Sampling random sampling.
2. Systematic random
sampling.
3. Stratified sampling
4. Area sampling
5. Cluster sampling
6. Multi-stage sampling
Sampling random sampling:
Sampling random sampling refers
to the sampling technique in
which each and every item of
the population is given an equal
chance of being included in the
sample.
Example:
Population size = 500
Sample ” = 50
(sampling interval) 500/50 = 10
Method used:
1. Lottery method
2. Table of random number
Types of probability sampling (Random Sampling)

16. Systematic random sampling:
In systematic sampling, only the
unit is selected and randomly and
the remaining units of the sample
are selected at fixed interval.
Example:
Population size = 1500 families
Sample size = 100 families
(Sampling interval) 1500/100=15
1st sample= 12th family
2nd ” = 12 +15/27 family
3rd ” = 27+15/42 family
Stratified sampling:
Under stratified sampling the
population is divided into several
sub-population that individually
more homogeneous than the
total population and then we
select items from each stratum to
constitute a sample.
Each sub-population is known “
strata” stratified is made according-
1. Economic condition-Rich,
middle class, poor or upper
middle class, lower middle
class.
2. 2. Social values- progressive
,conservative etc.
3. 3.Geographical location-
districts, upo-zilla etc.

17. Cluster sampling:
In cluster sampling the total
population is divided into a
number of relatively small
subdivisions which are
themselves clusters of still smaller
units and then some of these
clusters are randomly selected
for inclusion in the overall
sample.
Example: In Dhaka city, we can
not conduct a survey on "low
and order situation in that case
Dhaka city will be divided into a
member of areas or cluster, say
100 cluster, out of 100 cluster
sample will be selected at
random basis according to
homogeneity
Area sampling:
If clusters happen to be some geographic
subdivisions, in that case cluster sampling is
better known as area sampling.
Multi-stage sampling:
As the name implies this method refers to a
sampling procedure which is carried out in
several stages. Suppose, we want to take 5000
households from Bangladesh.
At the first stage- Bangladesh should be divided
into a member of districts and a few districts
selected at random.
At the second stage, each districts may be sub-
divided into a number of villages and a sample
of villages may be taken at random.
At the third stage, a number of households may
be selected from each of the villages selected
at the second stage. In this way, at each stage
the sample size becomes smaller and smaller.

18. Non-random sampling is that
sampling procedure which does
not afford any basis for estimating
the probability that each item in
the population has of being
included in the sample.
Types of non-random sampling:
1. Quota sampling
2. Judgment sampling
3. Convenience sampling
1. Quota sampling: Quota
sampling is a from of
proportionate stratified sampling,
in which a predetermined
proportion of people are
sampled from different groups,
but on a convenience basis.
Example: Maid survent-10%,
Housewife- 50%, Shopkeepers-
10%, Below 12 years- 10%,
Student-10%, Other-10% = 100%
Non-Random Sampling
2. Judgement sampling: In this type of
sampling items for the sample are selected
deliberation by the researcher purposively
choose the particular units of the universe
for constituting a sampling.
3. Convenience sampling: The method of
convenience sampling is also called the
chunk. A chunk is a fraction of one
population taken for investigation
because of its convenient availability.

19. Flowchart of the research process: This is cyclical
Research
Process
Research
begins with a
problem; an
unanswered
question in the
mind of
researcher
Research sees the
goal in a clear
statement
Research subdivides
the problem into,
appropriate sub
problem. Each sub
problem seeks
guidance through an
appropriate
hypothesis.
Research posits
tentative solutions
to the problems
through
appropriate
hypotheses. There
hypotheses direct
the researcher to
the facts.
Research looks
for facts directed
by the problem.
The facts are
collected and
organized.
Research interprets
the meaning of the
facts which leads to a
resolution of the
problem, thus
confirming or
rejecting an answer
to the question which
began the research
cycle.