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Adaptive Simple Random Sampling×Sampuli Iliyowekwa Ngazi×
NyanjaMetodolojia ya DodosoMetodolojia ya Dodoso
FamiliaProcess / pipelineProcess / pipeline
Mwaka wa asili1990–19921977
MwanzilishiSteven K. ThompsonWilliam G. Cochran
AinaProbability-based adaptive sampling designProbability-based survey sampling design
Chanzo asiliaThompson, S. K. (1992). Sampling. John Wiley & Sons. ISBN: 978-0471548850Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Majina mbadalaASRS, adaptive SRS, adaptive random sampling, sequential adaptive samplingProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Zinazohusiana52
MuhtasariAdaptive simple random sampling (ASRS) begins with a conventional simple random sample and then expands the sample in regions where the variable of interest exceeds a pre-specified threshold. Units neighboring a qualifying observation are added to the sample, allowing the design to concentrate effort where the population is dense or rare, while retaining unbiased estimation through the Horvitz-Thompson or Hansen-Hurwitz estimators. The approach was systematized by Steven K. Thompson in the early 1990s as part of the broader adaptive sampling framework.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.
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ScholarGateLinganisha mbinu: Adaptive Simple Random Sampling · Stratified Sampling. Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/compare