Process / pipelineSampling
Weighted Sampling — Weighted Probability Sampling
Weighted sampling is a probability-based design in which units are selected with unequal probabilities proportional to a known auxiliary measure of size or importance. Sampling weights — the inverse of inclusion probabilities — are applied during analysis so that each sampled unit correctly represents the population units it stands for. The approach underpins large-scale government, health, and social surveys where simple random sampling would be inefficient.
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Sources
- Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
- Horvitz, D. G., & Thompson, D. J. (1952). A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association, 47(260), 663-685. DOI: 10.2307/2280784 ↗
Related methods
Referenced by
Adaptive Weighted SamplingDisproportional cluster samplingDisproportional Stratified SamplingMulti-level weighted samplingOnline Weighted SamplingPilot Weighted SamplingProportional Simple Random SamplingProportional Weighted SamplingWeighted Quota SamplingWeighted Snowball SamplingWeighted Systematic SamplingWeighted Typical Case Sampling