Discussion Sampling Methods
GIS Group Meeting
San Lwin Htwe
GIS Specialist (UNODC)
What is Sampling?
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the process of selecting a small
number of elements from a
larger defined target group of
elements
the information gathered from
the small group will allow
judgments to be made about the
larger groups
Why sampling?
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Inability to analyze large quantities
of data potentially generated by a
population
Practical considerations such as cost
and time
Sampling can produce sound results
if proper rules are followed for the
draw
Basic concepts of Sampling
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Population
Sample
Sampling unit
Sampling error
Sampling frame
Sampling size
Basic concepts of Sampling
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Population: baseline the entire group under
study as defined by
objectives
Sample: a subset of
the population that
should represent the
entire group
Basic concepts of Sampling
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Sample unit: the basic level of investigation
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Sampling error:
same sampling methods, same population, the
study with a larger sample size will have less
sampling process error compared to the study
with smaller sample size
Basic concepts of Sampling
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Sampling frame:
a master list of the
population (total or
partial) from which the
sample will be drawn
Sampling size:
number of samples to
be drawn
Types of Sampling
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Probability
sampling
in which members of
the population have
a known chance
(probability) of
being selected
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Non-probability
sampling
in which the chances
(probability) of
selecting members
from the population
are unknown
Sampling methods
Probability
 Simple random
sampling
 Stratified random
sampling
 Systematic sampling
 Cluster sampling
Non-probability
 Convenience
sampling
 Judgment sampling
 Quota sampling
 Snowball sampling
Probability Sampling Methods
Simple random
method
every unit has an equal nonzero chance of being
selected
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Advantages:
 Known and equal chance
of selection
 Easy method when there
is an electronic database
Disadvantages:
 Complete accounting of
population needed
This method is the purest form of probability sampling
Probability Sampling Methods
Stratified random
method
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the population is separated
into homogeneous strata
and a sample is taken from
each
Advantages:
 More accurate overall
sample of skewed
population
Disadvantages:
 More complex sampling
plan requiring different
sample sizes for each
stratum
Often used when one or more of the stratums in the population
have a low incidence relative to the other stratums.
Probability Sampling Methods
Systematic
method
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the defined target population
is ordered and the sample is
selected according to
position using a skip interval
Advantages:
 Known and equal chance
of selected interval
 Less expensive…faster
than Radom methods
Disadvantages:
 Loss in sampling
precision
Systematic sampling is frequently used to select a specified
number of records from a computer file.
Probability Sampling Methods
Cluster method
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the population is divided into
groups (clusters), any of
which can be considered a
representative sample
Advantages:
 Economic efficiency …
faster and less expensive
 Does not require a list of
all members of the
population
Disadvantages:
 Cluster specification
error…
the more homogeneous the
cluster chosen, the more
imprecise the sample results
Non-probability Sampling Methods
Convenience
sampling method
the selecting on the basis of
convenience
the selection at familiar
locations and to choose
respondents who are like
themselves
often used during preliminary research efforts to get a gross
estimate of the results
Judgment method
selecting samples that
require a judgment or an
“educated guess”
must be confident that the chosen sample is truly representative
of the entire population.
Non-probability Sampling Methods
Quota sampling
method
samples that set a specific
number of certain types of
individuals
Often used to ensure desired
proportion of different
respondent classes
Snowball method
selecting samples which
require respondents to
provide the names of
additional respondents
special method used when the desired sample characteristic is
rare
Online Sampling Techniques
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Random online intercept sampling:
relies on a random selection of Web site visitors
Invitation online sampling:
is when potential respondents are alerted that they
may fill out a questionnaire that is hosted at a
specific Web site
Online panel sampling:
refers to consumer or other respondent panels that
are set up by marketing research companies for the
explicit purpose of conducting online surveys with
representative samples
Developing a Sampling
Plan
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Step-1
Define the relevant
population (baseline)
Step-2
Identify sample frame
Step-3
Determine specific
sampling method, all
necessary steps must
be specified
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Step-4
Determine sample size,
selecting samples
Step-5
Execute the sampling
Step-6
Sampling validation compare sample profile
with population profile
Re-sampling if
necessary
Factors to consider in
sampling design
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Work objectives
Degree of accuracy
Resources
Time frame
Knowledge on
population
Scope
Statistical analysis
needs
How to determine sample
size?
Common approaches for
determining sample size
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Budget/time available
Executive decision
Statistical methods
Historical data/guidelines
ISBN: 8173196257
Conclusions
Sampling is important for a survey/research project
Many sampling start with a general hope that something
interesting will emerge, and often end in frustration
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A well-designed sampling plan answers the
following questions –
What will be learned?
How long will it take?
How much will it cost?
http://www.surveysampling.com/
http://www.surveysystem.com/