Research
Methodology
Dr. Chowdhury Saleh Ahmed
1. Meaning of Research
Lecture 1
2. Objectives of Research
3. Motivation of Research
4. Types of Research
5. Research Approaches
6. Significance of Research
7. Research Methods and Research
Methodology
8. Criteria of good Research
9. Problems of research in countries
like Bangladesh
Meaning of Research
Research means an objective and systematic search for
pertinent information on a specific topic.
Example of Research:
• Carbon di oxide emission due to traffic jam
• Causes of crimes by slum dwellers etc
• Effectiveness of Educational incentive system for
controlling drop-outs
Cont..
•
Research has to be an original contribution to the
existing stock of knowledge.
Thus Research involves:
•
•
•
•
•
Enunciating the problem
Formulating the hypothesis
Collecting data/ facts/information
Analyzing the data/ facts/ information
Reaching at conclusions
Meaning of Research: Example
•
•
•
•
•
•
Problem: CO2- Traffic Jam is a health
hazardHypothesis – within tolerable limit
Collecting CO2 data through a sampling
procedure
Analyzing data whether within tolerable
limit
Making Conclusion
Objectives of Research
• To achieve new insights into a phenomenon
• To know about the existing phenomenon
• To know extent of a cause or effect
variables
• To establish relationship between variables
Motivation of Research: What
makes people undertake research
•
Desiring solution to the problem/ hazard
•
Desire to do a social / national /
organizational service
•
Inner satisfaction of a creative job
Types of Research
Descriptive versus Analytical :
Descriptive research means describing state
of affairs – Mostly involves primary data –
ex-post research
Analytical research means carrying out
analysis on a phenomenon – Mostly
involves secondary data – ex-ante researchbefore contemplated change
Cont.
• Applied versus Fundamental Research
• Applied research aims to find a solution to
an immediate problem facing a country/
society/ organization etc.
• Fundamental research is a basic research
mainly concerned with generalizations
Cont.
• Quantitative versus Qualitative Research
```Quantitative research is based on the
measurement of quantity or amount
```Example CO2 emission
`
```Qualitative research is concerned with subjective
attitude/ quality/ attributes / desires / feelings/ etc
```Example : Feeling about Dhaka city air pollution
( intolerable / Mildly intolerable / tolerable
Cont..
Conceptual versus Empirical
Conceptual research is about abstract ideas
or theory
Attack from ghosts,
Empirical Research is data-based and
subject to verification
Research Approaches
•
•
•
•
According to types of research discussed:
There can be two approaches to research:
Quantitative approach:
Qualitative approach
Cont….Research Approaches
• Quantitative approach can be further divided into
3 groups:
• Inferential approach – infer characteristics of a
phenomenon through collection of data –example
CO2 emission.
• Experimental approach – Researcher deliberately
changes some variables to know the causal effectexample – effect of temperature rise on plant
growth under open sky
Cont… Research Approaches
• Simulation approach – Researcher
artificially construct an environment and
collects data
• A greenhouse is constructed and impact of
temperature rise on plant growth is
measured
Significance of Research
“ Doubt is often better than
overconfidence as doubt leads to
enquiry and enquiry leads to
invention”
“ Research inculcates scientific and inductive
thinking that promotes development of
logical thinking”
Cont… Research Approaches
• Research provides the basis of all
government / international policies
• Research is used for solving various
problems of Businesses, NGOs, Societies
etc.
Research Methods and Research
Methodology
Research methods refer to use of
instruments for a research technique
Example:
Type of Research
Quantitative Field
Research
Methods of
Research
Questionnaire
Focussed Group
Discussion
Technique of Research
Researcher uses open and
close ended questions
Researcher selects a
particular group for the
detailed discussion
Cont… Research Methodology.
• Research methodology is a way to
systemically solve the research problem
• Research methodology has a broader
dimension than research methods
Cont.. Research Methodology
• Elements of Research Methodology are: Defining
objective
• Reviewing Literature
• Formulating Hypothesis
• Designing sample
• Collecting data
• Analyzing of data
• Arriving at conclusions
Criteria of good Research
• The objective of the research clearly defined
• The research methodology used should be
described in sufficient detail to permit another
researcher to repeat the research for further
advancement
• The sampling design should be such as to yield
least error
• The writing should be done with complete
frankness – nothing which has bearing on the
result should be hidden
Cont. Criteria of good Research.
• The validity and reliability of data as a well
as calculations should be re-checked to
avoid mistakes
• Conclusions should be confined to those
justified by data and analysis
• Researcher should be a person of integrity
Problems encountered in
countries like Bangladesh
• Insufficient interaction between Academics
and Practitioners
• Lack of training on the part of researchers
• Fear that information provided to
researchers may be used against them
• Secondary sources of data are not timely
available
Way forward to overcome
research problems in Bangladesh
• Greater interaction between academic institutions
and practicing organizations/ government/ NGOs
etc.
• More education and training on research
methodology
• National Policy on Research mentioning that
research data can not be used against the person
• Timely publication of secondary data and
enforcement of Act on “Right to Information”
The End
Lecture 2
Defining the Research Problem
Defining the Research problem is the first
step of Research Methodology or
Research process:
Defining
research
problem
Formulating Designing
Hypothesis sampling
technique
Collecting
Data
Analyzing
Data
Report
Writing
Research problem arises only
when:
•There must be group/individuals facing
the problem to be researched.
•There must be some objectives to be
achieved from the solution of the problems
•There may be alternative means of
obtaining the objectives
•Researcher must have some doubts about
the relative efficacy of the alternatives
Points to be observed in selecting a Research
Problem
•Subject on which research has been done should
not be chosen
•Controversial issues should be avoided
•Narrow or too wide issues should be avoided
•Research problem selected should be feasible
within means available
•Researcher should have some background
information on the research problems
Techniques of defining Research
problem
1. Statement of the Problem in a general way
2. Deep understanding the nature of the
problem
3. Surveying the available Literature
4. Developing the idea further through
discussion
5. Finally, Rephrasing the Research Problem
Techniques Involved in Defining
a Research Problem
Statement of the Problem
First of all the problem should be stated in a
general way
Understanding the nature of the problem
The researcher should be thoroughly knowlegible
in the subject
The researcher should first discuss the problem
with those who first raised the issue/ problem.
The researcher than should discuss the issue with
the resource persons excelling in the subject
Surveying the available Literature
All available research concerning the problem at
hand must necessarily be surveyed and examined
before formulating the research problem.
This means, the researcher must be well
conversant with available reports, records and
literature.
Developing the idea through
discussion
Discussion concerning a problem often
produces useful information.
People with rich experience are in a position to
enlighten the researcher on different aspects of
the proposal.
It helps sharpen the focus on specific aspects
of the research.
Rephrasing the Research Problem
Finally the researcher must rephrase the
research problem into a working proposition.
Once the nature of the problem has been
clearly understood, literature has been
reviewed,
discussion over the problem has taken place,
this rephrasing the research problem into
analytical / operational terms become
relatively easy.
Additional Points
• Technical terms and phrases with special
meanings should be clearly defined for
general readership.
• Basic assumptions relating to the research
problem should be clearly stated.
• Aim or value of the research should be
stated.
• The suitability of the time period and the
source of data availability should be
considered.
• The scope of investigation or the limits
within which the problem will be studied
need to be mentioned.
Example of a too broad /non-specific
topic:
Why is labour productivity lower in
Bangladesh compared to Vietnam
• Vague in terms of which sector
• Vague in terms of time frame
• Non-analytical – labour productivity
depends on certain factors -
Cont.
• Rephrasing:
• Factors responsible for productivity
differentials in Bangladesh and
Vietnam’s RMG sectors between 200510.
The End
Lecture 3
Research Design
• Research design is “decisions” regarding
what, where, when, how much, by what
means etc.
• It is management of conditions for
collection of data, analysis of data and
report preparation on the research problem.
Meaning of Research design
1. What is the study about?
2. Why the study is being undertaken?
3.
4.
5.
6.
Where will the study be carried out?
Where can the required data be found?
What will be the sample design
What period of time the study will include?
cont…
Cont… Meaning of Research design
7. What type of data is required?
8. What techniques of data collection will be
used?
9. How many items will be observed?
10. How will the data be analyzed?
11. In what format, the report will be prepared
within given time and budget?
Components of Research Design
•
1.
2.
3.
4.
From last two slides, it follows that Research Design
has five components:
Problem formulation and objective
Sampling design: design which deals with method of
selecting items to be observed in the given study. (3-6)
Observational design: design which relates to the
conditions under which the observations are to be
made on the selected items. (7- 8)
Statistical design: design that deals with how many
items will be observed and how information collected
will be analyzed. (9 - 10)
Cont..Components of Research
Design
• Operational design: design which deals with
the techniques by which procedures
specified in the sampling, observational
and statistical designs can be carried out.
Within given cost and time (11)
Research design must have:
1. Statement of the problem and objectives
2. Sources of information to be collected
(Sampling designs)
3. Types of information to be collected
(Observational designs)
4. Approach to be used for collecting and
analyzing data (Statistical designs)
5. Estimates of time and cost for the research
(Operational designs)
In Summary, Research design must
have
• Clear Statement of the Research Problem
and the objectives of research
• Sampling design
• Observational design
• Statistical design
• Operational design
Important Concepts Relating to
Research Design
Important Concepts Relating to
Research Design
•
•
•
•
•
Dependent and Independent Variables
Extraneous variable
Control variable
Research hypothesis
Testing significance of the result on
Research hypothesis
Dependent and Independent variable
• Variable – A concept/ entity that can take
different quantitative values is called a variable
• Continuous vs. discrete variable
• Example:
• Individual’s earning depends on his/her
knowledge and skill
• Here knowledge and skill is independent
variable
• Individual’s earning is dependent variable
Extraneous variable
• Variables not related to the study but affect
the dependent variable.
• Example - Measuring Dependency of Rice
yield to fertilizer doze in different districts.
• But soil types of different district would
affect yield- Soil types are extraneous
variables.
Control Variable
• Control variables are used to overcome the
effects of extraneous variables.
• Example: BRRI’s sub-stations in different
districts have experimental stations with
normal soil types and temperature – These
are used as control fields.
Research Hypothesis
• When a prediction or a hypothesized
relationship is tested by scientific methods,
it is termed as research hypothesis.
• The opposite of Research hypothesis is
known as null hypothesis.
Example of Research and Null
Hypothesis
Research Hypothesis:
Paddy yield depends positively on fertilizer
applied.
Null Hypothesis:
Paddy yield has no relationship at all with
fertilizer applied
The End
Lecture 4
Testing Significance of the Result
• Why done?
• Because a sample is taken rather than whole
population, therefore there is a need to test
significance or confidence on the result.
Testing Significance on the Result
• How it is done?
• Random Sample is said to be replica of the
Population’s
population.
distribution
Sample’s
distribution
2.5%
15% 25%
Mean
Height in
cm
2.5%
Testing Significance on the Result
If sample mean and standard deviation is
known and prior information on population
mean is available, then 95% confidence
interval can be calculated.
Formulating Research Problem
and
Objectives to be attained
• Survey of Literature
• Discussion with persons affected by the
problem, Resource persons
Sampling Design :
Relevant Terminology
•
•
•
•
Universe / Population –entire research area
Census – survey of entire population
Sample Survey – surveying a part of the
population
Sampling Frame - List of population from
which sample will be drawn
Sampling list – List of sampling units selected
Systematic Bias
Aim should be to avoid Systematic bias.
Systematic Bias occurs when:
•
•
•
•
•
Inappropriate sampling Frame
Defecting Measuring device
Non-respondents
Indeterminacy Principle
Natural bias
Sampling Errors
• Sampling Errors is the difference between the sample
estimate and the true population parameter.
• The sampling error can be found by subtracting the
value of a parameter from the value of a statistic.
• Example : Sample height – Population Height of
individuals
• Sampling error depends on sampling design.
Different Types of Sample
Design
• There are basically 2 types of Sampling:
• Probability sampling and Nonprobability sampling:
• Probability sampling
Sampling-
Random
• EACH SAMPLING UNIT HAS EQUAL
PROBABILITY
Non-probability sampling nonrandom samplingEACH SAMPLING UNIT HAS
UNEQUAL PROBABILITY,
Unrestricted vs. restricted sampling
• When each sample element is drawn
individually and directly from the
population at large, then sample drawn is
known as un-restricted sample.
• CHART SHOWING BASIC SAMPLING
Representation Basis
DESIGNS
Element
Selection
Probability
Sampling
Non-probability
Sampling
Simple Random
Sampling
Haphazard
sampling/
Convenience
sampling
Technique
Unrestricted
Restricted
Sampling
(Researcher’s
individual
judgment
involved)
Stratified Sampling
Purposive
sampling
(Researcher’s
individual
judgment involved)
(Researcher’s
individual
judgment
involved)
Probability Sampling
• Known also as Random / chance
sampling
• Here every item of the universe has an
equal chance of inclusion in the sample.
• All possible samples have equal chance of
inclusion
Cont.. Probability Sampling
• Therefore sample has the same
characteristics of the population- replica
of the population.
• Errors of estimation or significance of the
results can be measured.
The End
Procedure of selecting a random
sample
Lecture 5
• Suppose we have to randomly select 3
people from the class of 60 students.
• -----------------------------• 1-60 numbers corresponding to the students
are written in 60 pieces of paper
• These are folded so that numbers are not
seen
• The paper slips are thoroughly mixed
Procedure of selecting a random
sample
• Then 1 piece of paper is selected without seeing
the numbers written. The number is returned
to the pool.
• Then 2nd piece of paper is chosen and then the
3rd paper. If same no. is chosen, process is
repeated.
• Suppose 34, 03, 58 numbers/students are
chosen
• Each number and each possible sample (such
as 01, 60, 45, or 43, 06,55 has equal chance of
selection) (1/60 x 1/60 x 1/60)
Use of Random Table
47
91
82
28
81
95
70
89
73
48
10
4
41
40
86
27
46
80
20
58
24
97
52
75
35
23
8
53
34
11
31
15
2
83
44
9
43
63
71
22
93
32
7
51
50
21
1
74
14
64
19
69
12
55
39
59
92
79
30
42
33
99
62
26
13
45
60
84
90
68
49
85
36
5
94
18
3
87
16
100
54
61
56
65
96
29
88
25
72
17
98
6
38
78
66
76
37
77
67
57
Systematic sample: mix of
random and non-random
sampling
• Supposing, we have to chose 4 students
from 100 students.
• First a number from the random table is
selected
• Then 25 is added to the number to select
the next number. If total number exceeds
100 then move to the beginning.
Initial chosen
number and then
25 is added
successively.
Example
18
43
68
93
80
05
30
55
Advantage and disadvantage of
Systematic Sampling
Advantage
• Spread over evenly over the entire population
compared to random sample
• Easier and less costlier method
Disadvantage
If any systematic bias on the ith item (e.g.., 25th
item), it persists.
Otherwise, systematic sample is considered
equivalent to random sample,
Random Stratified Sampling
• Stratified sampling is used when the
population is not homogenous.
• Under Stratified sampling, more pertinent
information about the different homogenous
stratum is obtained and
• therefore better information for the whole
population is obtained.
Cont…
• However, various strata are to be formed in a
way so as to ensure that elements are most
homogenous within strata and most
heterogeneous between different strata.
• Otherwise no advantage from stratification
Cont. Random Stratified
Sampling
• Here, Strata are purposively formed and involves
past experience and personal judgment.
• Once strata are selected, selection of unit must be
done on random basis
• For better result, sampling units taken from each
strata should be proportion to the size of the strata.
Cluster sampling
• If total area of interest is large enough, area
can be divided into a number of nonoverlapping areas called clusters.
• The samples e.g., households are units in
these small areas or clusters.
Example
• Salinity prone areas subdivided into
different unions called clusters.
• Households belonging to the union can be
sampling units who could be interviewed.
Multi stage sampling- Two stage
Sampling
• Suppose we want to measure efficiency of Nationalized
Commercial Banks (NCBs) of Bangladesh:
• First stage is to randomly select some 2/3 divisions.
• Second we can select some districts randomly and
interview all bank managers of nationalized banks in
these districts.
Cont……………..
• This is two stage sampling.
• Divisions
• Districts
• Sampling units are bank branches
Multi stage sampling -Three
stage Sampling
• If instead of interviewing all bank managers
in the districts, we go down one step and
randomly select some towns in these
districts. We then interview all bank
managers of the towns.
Cont….
• Then this is a three-stage sampling.
• Divisions
• Districts
• Towns
Sampling units are bank branches
Multi-stage Sampling with
probability proportional to size
• Here Probability of inclusion of a cluster/
town is proportional to its size (in terms of
bank branches).
Example: Taking a sample of 10 branches
from a total of 500 branches spread over 15
towns so that probability of selecting a town is
proportional to size of the town (measured in
terms of branches)
• Number of bank branches in 15 towns are as
follows:
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15
35 17 10 32 70 28 26 19 26 66 37 44 33 29 28
• Table
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
35
17
10
32
70
28
26
19
26
66
37
44
33
29
28
35
52
62
94
164 192 218 237 263 329 366 410 443 472 500
10
60
110
160
210
Sequential number of
branch selected starting
with a random number 10
260 310 360 410
460
Cumulative branches
Comparison with Alternative sample
design: Simple Random Sample
Randomly choosing 10 branches from 500 branches
No assurance of rightly covering all divisions, districts,
and towns.
Bigger towns might have lower samples.
Complex/ Stratified sample is more
justified.
Non-Probability Sampling
• Non probability sampling is one where there is
no guarantee that sampling element has equal
probability of being selected.
• It is a kind of deliberate sampling.
• It is also known as purposive sampling.
• Example: For examining extreme poverty level
of draught prone area, some unions of Rangpur
is purposively chosen and compared with a
normal union of another district.
Limitation of Non-probability/
Purposive Sampling
• Researcher can purposively choose an area
which best suits his point of view.
• Element of human bias is always there
• Used in small scale research.
Conclusion
• Probability sampling should be attempted as it has
lowest bias and more importantly significance of
the result/ confidence on the result can be
estimated.
• If known characteristic of the population is known
before hand (so that test of significance can be
done), if probability sampling will not fully serve
the purpose and if the researcher has no bias
towards a particular result then purposive
sampling is suitable.
The End
DATA COLLECTION
TECHNIQUES
Lecture 6
Data-collection techniques allow us to
systematically collect information about our
objects of study (people, objects,
phenomena) and about the settings in which
they occur.
In the collection of data we have to be
systematic. If data are collected
inappropriately, it will be difficult to answer
our research questions in a conclusive way.
Example of Inappropriate data
Collection
• Suppose a research involves collecting data
of weight and age of infants living in a
particular rural area.
• However, if information on whether the
infant was suffering from any disease at the
time of observation was not collected,there
would be systematic error.
Various data collection
techniques can be used such as:
•
•
•
•
•
•
Using available information
Observing
Interviewing (face-to-face)
Administering written questionnaires
Focus Group Discussions
Projective Techniques, mapping etc.
1. Using available information
• Usually there is a large amount of data that
has already been collected by others,
although it may not necessarily have been
analysed or published.
• Locating these sources and retrieving the
information is a good starting point in any
data collection effort.
Cont…..
• The use of key informants is another important
technique to gain access to available information.
• Key informants could be knowledgeable persons
who has knowledge of the sources of available
information.
• They can be involved in various stages of the
research, from the statement of the problem to
analysis of the data and development of
recommendations.
2. Observing
• OBSERVATION is a technique that
involves systematically watching and
recording behaviour and characteristics of
living beings, objects or phenomena.
• Observation of human behaviour is a
much-used data collection technique. It can
be undertaken in different ways:
Cont….
• Participant observation: The observer
takes part in the situation he or she
observes. (For example, a doctor
hospitalized with a broken hip, who now
observes hospital procedures ‘from within’.)
• Non-participant observation: The
observer watches the situation, openly or
concealed, but does not participate.
Cont…
• Observations can also be made on objects.
For example, the presence or absence of a
latrine and its state of cleanliness may be
observed. Here observation would be the
major research technique.
Used for RMG Compliance requirements
for export to USA / EU
Cont…..
• If observations are made using a defined
scale they may be called measurements.
• Measurements usually require additional
tools.
• For example, in nutritional surveillance we
measure weight and height by using
weighing scales and a measuring board. We
use thermometers for measuring body
temperature
3. Interviewing
• An INTERVIEW is a frequently used datacollection technique that involves oral
questioning of respondents, either individually
or as a group.
• Answers to the questions posed during an
interview can be recorded by writing them
down (either during the interview itself or
immediately after the interview) or by taperecording the responses, or by a combination
of both.
Cont…
• Interviews can be conducted with
varying degrees of flexibility. The two
extremes, high and low degree of
flexibility, are described below:
High degree of flexibility:
• When studying sensitive issues such as
teenage pregnancy and abortions in slum
areas, the investigator may use a list of
topics rather than fixed questions.
• Examples are:
• Responsibility of girls and their partners to
prevent teenage pregnancy,
• actions to be taken once there there is
unwanted pregnancies etc.
Cont…
• The sequence of topics should be
determined by the flow of discussion.
• It is often possible to come back to a topic
discussed earlier in a later stage of the
interview to gather needed information.
Low degree of flexibility:
• Less flexible methods of interviewing are
useful when the researcher is relatively
knowledgeable about expected answers or
when the number of respondents being
interviewed is relatively large.
• Then questionnaires may be used with a
fixed list of questions in a standard
sequence, which have mainly fixed or precategorized answers.
Administering written
questionnaires
• A WRITTEN QUESTIONNAIRE (also
referred to as self-administered
questionnaire) is a data collection tool in
which written questions are presented that
are to be answered by the respondents in
written form.
Cont..
•
A written questionnaire can be
administered in different ways, such as by:
1. Sending questionnaires by mail with clear
instructions on how to answer the
questions and asking for mailed responses;
Cont…
2. Gathering all or part of the respondents in
one place at one time, giving oral or
written instructions, and letting the
respondents fill out the questionnaires;
3. Hand-delivering questionnaires to
respondents and collecting them later.
5. Focus group discussions
(FGD)
• A focus group discussion allows a group of
8 - 12 informants to freely discuss a
certain subject without restraint under the
guidance of the researcher /facilitator.
Cont.
• Focused group discussions are done
specially when inter-group sensitivity
exists.
• Example: Tenant farmer and Owner farmer
• Tenant farmer would not mention about
exploitative behaviors of Owner farmers if
the later are present in the same group
6. Projective techniques
• When a researcher uses projective
techniques, he / she asks an informant to
react to some kind of visual or verbal
stimulus.
• For example: An informant may be
provided with a rough outline of the body
and be asked to draw his/her illness.
Mapping
• Mapping is a valuable technique for visually
displaying relationships and resources.
• In a water supply project, for example, mapping
is invaluable. It can be used to present the
placement of wells, distance of the homes from
the wells, other water systems, etc.
• It gives researchers a good overview of the
physical situation and may help to highlight
proper selection of a new water source.
Difference between Data
collection techniques and tools
Data Collection
Techniques
Data Collection Tools
Using available information
Checklists, Data compilation forms.
Observing
Eyes and other senses, pen/paper,
watch, scales etc.
Interview guide, checklist,
questionnaire, tape recorder
Interviewing
Administering written
questions
Questionnaire
Techniques
Advantages Disadvantage
.
Using available Is inexpensive,
information
because data is
already there
Permits examination
of trends over the
past.
Observing
Permits collection of
information on facts not
mentioned in an interview.
Permits tests of reliability of
responses to questionnaire
Data is not easily
available.
Information may
not be fully
appropriate
Presence of data
collector may influence
result
Ethical issues regarding
privacy may arise.
Techniques
Advantages Disadvantage
.
Interviewing
Is suitable for use with
both literates and
illiterates.
Permits clarification
of questions.
Has higher response
rate than written
questions
The presence of the
interviewer can
influence responses.
Reports of events
may be less
complete than
information gained
through
observations.
Techniques
Advantages Disadvantage
.
Flexible
interview
Permits collection of
in-depth information
and exploration of
spontaneous remarks
by respondents
Fixed interview Easy to analyze
.Interview may
inadvertently
influence the
respondents.
Analysis of openended data is more
difficult and time consuming
Important information
may be missed
Techniques
Advantages Disadvantage
.
Administering
written
questionnaire
Is less expensive
Permits anonymity
and may result in
more honest
responses.
Eliminates bias due to
phrasing questions
differently with
different respondents.
Cannot be used with
illiterate
respondents.
There is often a low
rate of responses.
Questions may be
misunderstood.
Techniques
Advantages Disadvantage
.
Participatory
and projective
methods
Provide rich data and
may have positive
spin offs for
knowledge and skills
by researchers and
informants.
Require some extra
training of
researchers.
Guidelines for Development of
Questionnaire
• Problem/ issue to be studied must be kept in
view
• Type of analysis to be done would dictate
data to be collected.
• Draft questionnaire to be framed first. After
a pilot survey, this is to be finalized.
• Questions should be simple without
ambiguity.
Guidelines for Interviewing
• Researcher/Interviewer should be aware of the
problem being researched. Training to be given to
the interviewer.
• User-friendly and informal approach to be used.
• Interview atmosphere should be normal.
• Interviewer has to establish proper rapport with
interviewee for a two-way communication.
The End
Individual Assignment
1.
2.
3.
4.
5.
Formulate a research problem of your. choice (should
involve primary data collection).
Formulate research objectives (benefits of the research).
Formulate research / null hypotheses to be tested.
Design sampling procedure.
Design data collection (type of data to be collected and
how).
In maximum 2 pages ( single space typed).
Time allowed :2 weeks (15th February, 2011).