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Клъстерно извадково изследване×Ранжирано извадково вземане (Ranked Set Sampling)×
ОбластМетодология на проучваниятаИзвадка
СемействоProcess / pipelineProcess / pipeline
Година на възникванеEarly-to-mid 20th century; canonical treatment 1953/19771952
СъздателFormalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practiceGlenn A. McIntyre
ТипProbability sampling designSampling design methodology
Основополагащ източникCochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407McIntyre, G. A. (1952). A method for unbiased selective sampling using ranked sets. Australian Journal of Agricultural Research, 3(4), 385–390. DOI ↗
Други названияcluster random sampling, area sampling, one-stage cluster samplingRSS
Свързани54
РезюмеCluster sampling is a probability sampling technique in which the population is divided into naturally occurring groups (clusters), a random sample of clusters is selected, and all — or a random subset of — members within each selected cluster are studied. It is especially practical when a complete population list is unavailable or when units are geographically dispersed, making individual random selection prohibitively expensive. One-stage cluster sampling surveys every member of selected clusters; two-stage designs add a second random draw within clusters.Ranked Set Sampling (RSS) is a data collection method introduced by G. A. McIntyre in 1952 that improves estimation efficiency when visual ranking of units is easier or cheaper than actual measurement. By deliberately selecting and measuring units that are ranked as most likely to yield desired outcomes, RSS reduces variance compared to simple random sampling while maintaining unbiasedness.
ScholarGateНабор от данни
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ScholarGateСравнение на методи: Cluster Sampling · Ranked Set Sampling. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare