Comparar métodos

	Amostra Ponderada	Amostra Estratificada Proporcional
Área	Metodologia de survey	Metodologia de survey
Família	Process / pipeline	Process / pipeline
Ano de origem	1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator)	1953–1965 (formalized in survey sampling literature)
Autor original	Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework)	William G. Cochran; Leslie Kish
Tipo	Probability sampling design	Probability sampling design
Fonte seminal	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
Outros nomes	probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling	proportionate stratified sampling, proportional allocation stratified sampling, PSRS, proportionate stratified random sampling
Relacionados	6	6
Resumo	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.	Proportional stratified sampling divides the target population into non-overlapping strata (subgroups defined by a key characteristic such as age band, region, or gender) and then draws a simple random sample from each stratum so that each stratum's share of the total sample matches its share of the total population. Because each subgroup is represented in exact proportion to its population weight, the resulting sample mirrors the population structure closely without requiring post-hoc weighting adjustments.