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Échantillonnage stratifié pondéré×Échantillonnage stratifié×
DomaineMéthodologie d'enquêteMéthodologie d'enquête
FamilleProcess / pipelineProcess / pipeline
Année d'origine1953–19651977
Auteur d'origineLeslie Kish; William G. CochranWilliam G. Cochran
TypeProbability sampling with weightingProbability-based survey sampling design
Source fondatriceCochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Aliasstratified sampling with weights, design-weighted stratified sampling, post-stratification weighting, WSSProportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Apparentées62
RésuméWeighted stratified sampling divides a population into non-overlapping strata and draws a probability sample from each stratum, then attaches a design weight to every selected unit so that estimates correctly represent the full population. Weights compensate for unequal selection probabilities that arise from disproportionate stratum allocations, non-response, or frame imperfections, making the procedure the backbone of most large-scale national and international surveys.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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ScholarGateComparer des méthodes: Weighted Stratified Sampling · Stratified Sampling. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare