Comparer des méthodes

	Échantillonnage stratifié pondéré	Échantillonnage à plusieurs degrés
Domaine	Méthodologie d'enquête	Méthodologie d'enquête
Famille	Process / pipeline	Process / pipeline
Année d'origine	1953–1965	1950s–1960s (formalized in Kish 1965 and Cochran 1977)
Auteur d'origine	Leslie Kish; William G. Cochran	Leslie Kish; William G. Cochran
Type	Probability sampling with weighting	Probability sampling design
Source fondatrice	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495
Alias	stratified sampling with weights, design-weighted stratified sampling, post-stratification weighting, WSS	multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling
Apparentées	6	5
Résumé	Weighted 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.	Multistage sampling is a probability-based design that selects a sample by working through two or more successive levels of a population hierarchy — for example, first selecting regions, then districts within those regions, then households within those districts. It makes large-scale surveys practical when a complete population list is unavailable or when the population is geographically dispersed, by concentrating fieldwork within a manageable number of sampled units at each stage.