Survey sampling
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In statistics, survey sampling is random selection of a sample from a finite population. It is an important part of planning statistical research and design of experiments. Sophisticated sampling techniques that are both economical and scientifically reliable have been developed.
An entire industry of public opinion polling as well as the technical activities of the U.S. Bureau of the Census depends on these techniques.
The most elementary methodology is called simple random sampling. Most of the theory of statistics assumes this kind of sampling unless otherwise noted. In theory it ensures that all subsets of the population are given a balanced probability of selection.
The possibility of very expensive or very atypical samples has led to a variety of modifications such as stratified sampling, cluster sampling, and multistage sampling.
In public opinion polling by private companies or organizations unable to require response, the resulting sample is self-selected rather than random. Volunteering for the sample may be determined by characteristics such as submissiveness or availability. The samples in such surveys are therefore non-probability samples of the population, and the validity of estimates of parameters based on them is unknown. Generally, the survey is designed to minimise such bias, such that it can reasonably be assumed that the sample is close enough to random, to be treated as such.
See also
External links
- U.S. Bureau of the Census
- University of Michigan Survey Research Center
- Journal of Information Technology Learning and Performance article Organizational Research: Determining Sample Size in Survey Research
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