Sampling design

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

Mathematically, a sampling design is denoted by the function P(S) which gives the probability of drawing a sample S.

[edit] An example of a sampling design

During Bernoulli sampling, P(S) is given by

P(S) = q^{N_\text{sample}(S)} \times (1-q)^{(N_\text{pop} - N_\text{sample}(S))}

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

[edit] See also

[edit] Further reading

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


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