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OblastMetodologija anketaUzorkovanjeMetodologija anketaMetodologija anketa
PorodicaProcess / pipelineProcess / pipelineProcess / pipelineProcess / pipeline
Godina nastankaEarly-to-mid 20th century; canonical treatment 1953/197719521977Mid-20th century (Cochran 1953; Kish 1965)
TvoracFormalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practiceGlenn A. McIntyreWilliam G. CochranWilliam G. Cochran; formalized in survey sampling theory
TipProbability sampling designSampling design methodologyProbability-based survey sampling designProbability sampling design
Temeljni izvorCochran, 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 ↗Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Drugi nazivicluster random sampling, area sampling, one-stage cluster samplingRSSProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örneklemeinterval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
Srodne5425
SažetakCluster 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.Stratified sampling is a probability sampling design in which the target population is partitioned into non-overlapping, exhaustive subgroups called strata, and independent probability samples are drawn within each stratum. Formalized by William G. Cochran in Sampling Techniques (1977), the method exploits known population structure to reduce variance and guarantee representativeness of all major subgroups, making it a cornerstone of large-scale survey research and official statistics.Systematic sampling is a probability sampling technique in which every k-th element is selected from an ordered list of the population after a random starting point. With population size N and desired sample size n, the sampling interval k = N/n is computed and one unit is chosen at random from the first interval; all subsequent units are selected by adding k repeatedly. The method is operationally simple, yields a spread-out sample, and often achieves lower variance than simple random sampling when the list has no harmful periodicity.
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ScholarGateUporedite metode: Cluster Sampling · Ranked Set Sampling · Stratified Sampling · Systematic Sampling. Preuzeto 2026-06-17 sa https://scholargate.app/sr/compare