Comparar métodos

	Amostragem Ponderada Proporcional	Amostragem por Conglomerados
Área	Metodologia de survey	Metodologia de survey
Família	Process / pipeline	Process / pipeline
Ano de origem	Mid-20th century (formalized 1950s–1960s)	Early-to-mid 20th century; canonical treatment 1953/1977
Autor original	William G. Cochran; Leslie Kish	Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice
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.). Wiley. ISBN: 978-0471162407
Outros nomes	proportional probability weighting, proportional weight sampling, probability proportional to size sampling, PPS sampling	cluster random sampling, area sampling, one-stage cluster sampling
Relacionados	6	5
Resumo	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.	Cluster sampling is a probability sampling technique in which the population is divided into naturally occurring groups (clusters), a random sample of clusters is selected, and all — or a random subset of — members within each selected cluster are studied. It is especially practical when a complete population list is unavailable or when units are geographically dispersed, making individual random selection prohibitively expensive. One-stage cluster sampling surveys every member of selected clusters; two-stage designs add a second random draw within clusters.