In the theory of finite population sampling, a sampling design specifies for every possible sample its probability of being drawn.

Mathematical formulation

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Mathematically, a sampling design is denoted by the function   which gives the probability of drawing a sample  

An example of a sampling design

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During Bernoulli sampling,   is given by

 

where for each element   is the probability of being included in the sample and   is the total number of elements in the sample   and   is the total number of elements in the population (before sampling commenced).

Sample design for managerial research

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In business research, companies must often generate samples of customers, clients, employees, and so forth to gather their opinions. Sample design is also a critical component of marketing research and employee research for many organizations. During sample design, firms must answer questions such as:

  • What is the relevant population, sampling frame, and sampling unit?
  • What is the appropriate margin of error that should be achieved?
  • How should sampling error and non-sampling error be assessed and balanced?

These issues require very careful consideration, and good commentaries are provided in several sources.[1][2]

See also

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References

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  1. ^ Salant, Priscilla, I. Dillman, and A. Don. How to conduct your own survey. No. 300.723 S3.. 1994.
  2. ^ Hansen, Morris H., William N. Hurwitz, and William G. Madow. "Sample Survey Methods and Theory." (1953).

Further reading

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  • Sarndal, Swenson, and Wretman (1992), Model Assisted Survey Sampling, Springer-Verlag, ISBN 0-387-40620-4