Comparer des méthodes

	Échantillonnage pondéré proportionnel	Échantillonnage pondéré
Domaine	Méthodologie d'enquête	Méthodologie d'enquête
Famille	Process / pipeline	Process / pipeline
Année d'origine	Mid-20th century (formalized 1950s–1960s)	1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator)
Auteur d'origine	William G. Cochran; Leslie Kish	Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework)
Type	Probability sampling design	Probability sampling design
Source fondatrice	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Alias	proportional probability weighting, proportional weight sampling, probability proportional to size sampling, PPS sampling	probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling
Apparentées	6	6
Résumé	Proportional weighted sampling is a probability-based survey design in which each subgroup (stratum or cluster) of the population is sampled and weighted in proportion to its true size in the population. By assigning sampling weights that mirror the actual composition of the population, the method ensures unbiased estimates without the need for post-hoc reweighting, and produces efficient estimates when variance within subgroups is relatively homogeneous.	Weighted sampling is a probability-based design in which units are selected with unequal probabilities proportional to a known auxiliary measure of size or importance. Sampling weights — the inverse of inclusion probabilities — are applied during analysis so that each sampled unit correctly represents the population units it stands for. The approach underpins large-scale government, health, and social surveys where simple random sampling would be inefficient.