Discussion Sampling Methods

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

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

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

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

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

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

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

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

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 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

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.

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.

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

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.

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
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
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

Factors to consider in sampling design
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
Budget/time available Executive decision Statistical methods Historical data/guidelines ISBN:

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?