Difference between revisions of "Probability Sampling"

From knowledgebase
Jump to navigation Jump to search
Tag: Replaced
 
Line 1: Line 1:
−
Probability Sampling
+
The essential characteristic of probability sampling is a procedure where each person or item is given a known chance of inclusion and the procedure is used for the selection of individual items in the [[Population|Population]]. Possible methods are:
 +
 
 +
* Random sampling
 +
** Each individual has an equal chance of being selected.
 +
** Make sure more people are selected
 +
* Stratification
 +
** If certain groups (or strata) can be identified before sample selection takes place it will be better to include this upfront. This is called stratification.
 +
** When you do not know the groups upfront you can identify those by asking a question:
 +
*** "At the last general election which party did you vote for"
 +
*** "Do you ride a motor cycle"
 +
** The retrospective use of information is known as post stratification.
 +
* Cluster Sampling
 +
** If your population has a group or clusters which adequately represent the whole population it is more convenient and cost effective to select a random cluster and carry out a census for a complete cluster. This is called cluster sampling.
 +
** An interesting variant of cluster sampling is a ''random walk''. For instance, conduct interviews with every 5th house.
 +
 
 +
With ''multistage design'' a series of related samplings are conducted.
 +
 
 +
 
 +
Part of: [[M7-Quantitative Decision Methods-S1 - Managing Data and Survey Methods|M7-Quantitative Decision Methods-S1 - Managing Data and Survey Methods]]
 
[[Category:mbi]]
 
[[Category:mbi]]
  

Latest revision as of 20:01, 27 August 2020

The essential characteristic of probability sampling is a procedure where each person or item is given a known chance of inclusion and the procedure is used for the selection of individual items in the Population. Possible methods are:

  • Random sampling
    • Each individual has an equal chance of being selected.
    • Make sure more people are selected
  • Stratification
    • If certain groups (or strata) can be identified before sample selection takes place it will be better to include this upfront. This is called stratification.
    • When you do not know the groups upfront you can identify those by asking a question:
      • "At the last general election which party did you vote for"
      • "Do you ride a motor cycle"
    • The retrospective use of information is known as post stratification.
  • Cluster Sampling
    • If your population has a group or clusters which adequately represent the whole population it is more convenient and cost effective to select a random cluster and carry out a census for a complete cluster. This is called cluster sampling.
    • An interesting variant of cluster sampling is a random walk. For instance, conduct interviews with every 5th house.

With multistage design a series of related samplings are conducted.


Part of: M7-Quantitative Decision Methods-S1 - Managing Data and Survey Methods