Comparar métodos

	Amostra Ponderada	Amostragem Estratificada
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)	1977
Autor original	Morris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework)	William G. Cochran
Tipo	Probability sampling design	Probability-based survey 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.). Wiley. ISBN: 978-0-471-16240-7
Outros nomes	probability proportional to size sampling, PPS sampling, unequal probability sampling, importance sampling	Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Relacionados	6	2
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.	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.