2. SESSION OBJECTIVES
The session will cover the following areas
• population
• sampling and sampling techniques
• Data collection instruments
• Data collection procedures
3. Population and sample
• A population is a complete collection (or
universe) of all the elements (units) that are of
interest in a particular investigation.
• A Sample: is a collection of some (a subset)
the elements of a population..
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4. Population and Sample
• Target population- this is the population to
which the research ultimately wants to
generalize his results
• Sampled population- this is the accessible
population. It the population from which the
sample will be drawn
• A sample is the elements within the sampled
population that take part in the study
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5. Census
• When one wants to study the entire
population, then he is dealing with a census
• Under the census or complete enumeration
survey method, data are collected for each
and every unit [person, household, field,
shop, factory etc.] of the population or
universe
• A census has several advantages
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6. Advantages & disadvantages of a
census
• Data obtained from each and every unit of
the population
• The results obtained are likely to be more
representative, accurate and reliable
Costly
Time consuming
Sometimes not necessary
That’s why normally samples are used
7. What is Sampling?
• Sampling: is the process of selecting elements
from a population in such a way that the
sample elements selected represent the
population
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8. Sampling
Advantages of sampling
• Reduced time and cost needed to collect data
• More comprehensive data is obtained than in
a census
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9. sampling
Disadvantages of sampling
• The selected units may not be representative
of the population especially when the sample
size is small.
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10. Sampling process
• Sampling process involves five steps
• Defining the population
• Listing the elements of the population(sample
frame)
• Determine the appropriate sampling
methodology
• Decide on the appropriate sample size
• Select a representative sample
11. Types of samples
• Representative sample also known as
probabilistic sampling
• A representative sample is similar to the
population in all important ways.
• It is selecting a sample in a way that gives
every element in the population a chance to
be selected
12. Non-representative samples
• Also called Non probabilistic sampling
• Not truly representative
• based on subjective judgment of the
researcher.
• Here the researcher decides on the elements
to be included in the sample
• Less desirable than probability samples.
14. Categories of Representative
/probabilistic Samples
Random sample
• Each individual in the population of interest has an
equal likelihood and or chance of selection.
• Each possible sample of a given size has a known
and equal probability of being the sample actually
selected.
• Every element is selected independently of every
other elements
• It can be done by use of lottery method or random
method
15. Systematic Random sampling
• The sample is chosen by selecting a random starting
point and then picking every i th
element in succession
from the sampling frame.
• The sampling interval, i, is determined by dividing the
population size by the sample size and rounding to
the nearest if it not a full number e.g you want to
study 20 house holds out of a hundred 100/20= 5.
five becomes your interval. Every fifth house hold
will be selected
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16. Stratified Samples
• A stratified sample is a mini-reproduction of
the population.
• Before sampling, the population is divided
into characteristics of importance for the
research e.g Males and Females, married and
not married, Blacks, Whites and Colored e.t.c
17. cotd
• The strata should be mutually exclusive and
collectively exhaustive. In that every
population element should be assigned to one
and only one stratum and no population
elements should be omitted
• Elements are then selected from each stratum
by a random procedure.
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18. Types of Stratified random
sampling
• Proportionate stratified random sampling; taking
proportionate samples from the population
irrespective of inequality in number e.g out 100
DLTM participants 40 are ladies 60 gentlemen and
you want a sample of 20. 40/100 X20 =8 ladies,
60/100 X20 =12 gentlemen
• Disproportionate stratified random sampling. you
take samples that not proportionate e.g. 10 ladies
and 10 gentlemen of more ladies if interested in
female related issues. OR you may pick 15 ladies and
5 gentlemen if you think ladies have the information
you need
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19. Cluster random sampling
• This is a sampling methodology in which
elements of a population are grouped into
clusters and simple random sampling then
performed on clusters.
• Clustering is similar to stratification in that
both involve partitioning the population into
subgroups.
• It is different in that the sampling cluster is
heterogeneous.
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20. Cluster sampling
• Cluster sampling can be done in stages and
this is called multistage sampling. E.g you may
want to study causes of poverty in uganda.
You multistage cluster uganda into several
clusters;
• Regions
• Districts
• Sub counties
• E.t.c
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21. Types of Non-representative/non
probabilistic samples
• Quota Sample
• In this type of sampling the researcher is
given definite instructions about the section
of the public he is to question,
• However the final choice of the actual
persons is left to his own convenience and is
not predetermined
22. Judgmental sampling
Also referred to as Purposive sampling
• Non-representative subset of some larger
population
• Constructed to serve a very specific need or
purpose.
• The researcher chooses subjects who in his
opinion are likely to supply information
relevant to the research problem
23. Snowball Sample
• A snowball sample is achieved by asking a
participant to suggest someone willing or
appropriate for the study.
• Snowball samples are particularly useful in
hard-to-track populations
24. Convenience or Accidental Sample
• A convenience sample is a matter of taking
what you can get.
• In this method respondents are selected
because they happen to be in the right place
at the right time
25. In Summary;
Step 1: Define the
the target population
Step 2: Select
The Sampling
Frame
Step 3: Probability
OR Non-probability?
Step 4: Plan
Selection of
sampling
units
Step 5: Determine
Sample Size
Step 6: Select
Sampling units
Step 7: Conduct
Fieldwork
26. Sampling Error
sampling errors: a measure of the
difference between a statistic and the
parameter it is estimating
• These arise when the sample of the
population surveyed is not representative of
the population from which it is drawn.e.g
sampling internet users in kampala and your
sample has only university students
27. Non Sampling errors
• Wrong concepts
• Coverage errors-omission of a unit in a sampling
frame
• Errors due to misunderstanding the questions
• Response errors-wrong responses
• Non response errors
• Questionnaires not understood
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28. Data Collection methods
• These are methods of collecting information from the
field.
• The methods are determined by type of data to be
collected
– Primary vs secondary data
– Qualitative vs quantitative data
• There are four ways of gathering data:
• Questionnaires
• Literature study
• Observation
• interviews
29. questionaire
• It is a carefully constructed instrument that
consists of a set of questions to which the
subject responds to in writing
• Questionnaires can be close ended or open
ended
30. Using Open-Ended Questions
Common when the researcher cannot
anticipate people’s responses or
If listing all possible major responses is
impractical.
Effective for stimulating thought, probing for
complex questions
31. cotd
• Quite valuable in exploratory research.
• Very demanding for respondents.
• Responses to such question can be
difficult to classify and code.
32. Closed Ended questions
• Responses are forced into fixed categories
• Potentially very demanding on side of
researcher.
• Major complaint…not all relevant options
are stated.
33. Questionnaire
Construction
Questions must give you enough
information to accomplish your objectives
Questions must stated to enable
respondents to provide accurate answers.
34. Question Wording
Keep wording simple and
straightforward…
If sampling certain groups (occupational
groups), complex wording (professional jargon)
may be necessary to facilitate communication &
credibility.
35. cotd
–Wording for more sensitive questions
should be carefully designed.
–Be extra careful in developing questions
designed to obtain information on
attitudes and beliefs.
36. Question Wording
Aim for Clarity: vague questions produce
vague answers.
Avoid biased or leading questions.
Avoid double-barrelled questions.
37. Literature study /document
analysis
• Method of data collection that involves
analysis of documents.
• These could be text books, magazines,
financial reports, attendance registers e.t.c
38. observation
• Observation Means seeing or viewing.
• Observation can be of different types.
• Participant observation where the observer is part
of the phenomenon or group, which is being
observed, and he acts as both an observer and a
participant.
• Non-participant observation where the observer
stands apart and does not participate in the
phenomenon being observed.
39. Advantages
– It enables the researcher to study behavior as it
occurs and this makes the data more reliable and
free from respondent’s bias
– It is the only method, which can be used when the
participants cannot express themselves
meaningfully e.g. children, the very sick, the mob,
those in riots etc
– If the individual is unwilling to be interviewed or
fill in questionnaires
40. advantages
– The researcher can adjust the goals and objectives
of the study as the data is being collected.
– Observation provides a richer and more direct
account of the phenomenon and a study as a
whole since behavior is taking place in its natural
environment
41. Disadvantages
• The researcher has to wait until the
phenomenon or event takes place
• It is difficult to have a random or
representative sample, which is needed in the
sample
• Compared to interviewing it might be less
expensive in terms of money and equipment
but it costs more man-hours spent in the field
and requires personal adoption to the
conditions of the field
42. Disadv cotd
• It cannot be used to study attitudes and
opinions
• Observed data is difficult to compress,
quantify or reduce to codes which can be
tabulated or processed by a computer
• Observer fatigue could easily set in and distort
our observation
43. interviews
• In the interview, the researcher talks to the
respondent and obtains information directly.
44. Advantages
• Flexible.
• In-depth.
• Situation can be adapted.
• Reasons for answers can be sought.
• Clues can be followed up.
• Yields a higher percentage of answering.
46. Focus Group discussions
• Focus Group: An interview conducted among
a small number of individuals simultaneously;
the interview relies more on group discussion
than on directed questions to generate data.
• Characteristics of Focus Groups
• Typically 8 – 12 people
• Homogeneous within group
• 1.5 to 2 hours in length
• Sessions recorded and transcribed
47. Further reading
• Research is never conclusive, please read
more
• Amin, E. M. (2005). Social Science research:
conception, methodology and analysis. Makerere
University printery. Kampala
• Neuman, W.L. (2003). Social Research Methods:
Qualitative and Quantitative Approaches. Fifth
Edition Pearson Education; Inc. 2003 Boston, USA
