1. Discussion Sampling Methods
GIS Group Meeting
San Lwin Htwe
GIS Specialist (UNODC)

2. What is Sampling?
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

3. Why sampling?
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

4. Basic concepts of Sampling
Population
Sample
Sampling unit
Sampling error
Sampling frame
Sampling size

5. Basic concepts of Sampling
Population: baseline -the entire group under study as defined by objectives
Sample: a subset of the population that should represent the entire group

6. Basic concepts of Sampling
Sample unit: the basic level of investigation
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

7. Basic concepts of Sampling
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

8. Types of Sampling Probability sampling
in which members of the population have a known chance (probability) of being selected
Non-probability sampling
in which the chances (probability) of selecting members from the population are unknown

9. Sampling methods Probability Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
Non-probability
Convenience sampling
Judgment sampling
Quota sampling
Snowball sampling

10. Probability Sampling Methods
Simple random method
every unit has an equal non-zero chance of being selected
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

11. Probability Sampling Methods
Stratified random method
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.

12. Probability Sampling Methods
Systematic method
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.

13. Probability Sampling Methods
Cluster method
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

14. 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
Judgment method
selecting samples that require a judgment or an “educated guess”
often used during preliminary research efforts to get a gross estimate of the results
must be confident that the chosen sample is truly representative of the entire population.

15. 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

16. Online Sampling Techniques
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

17. Developing a Sampling Plan
Step-1
Define the relevant population (baseline)
Step-2
Identify sample frame
Step-3
Determine specific sampling method, all necessary steps must be specified
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

18. Factors to consider in sampling design
Work objectives
Degree of accuracy
Resources
Time frame
Knowledge on population
Scope
Statistical analysis needs

19. How to determine sample size?

20. Common approaches for determining sample size
Budget/time available
Executive decision
Statistical methods
Historical data/guidelines
ISBN:

21. 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
A well-designed sampling plan answers the following questions –
What will be learned?
How long will it take?
How much will it cost?