Porovnat metody

	Adaptivní stratifikovaný výběr	Systematický výběr
Obor	Metodologie dotazníkových šetření	Metodologie dotazníkových šetření
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	1990s (formal development from Thompson 1990 onward)	Mid-20th century (Cochran 1953; Kish 1965)
Tvůrce	Steven K. Thompson (adaptive sampling); allocation adaptations by Salehi, Seber, and others	William G. Cochran; formalized in survey sampling theory
Typ	Probability-based adaptive sampling design	Probability sampling design
Původní zdroj	Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412), 1050–1059.	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Další názvy	ASS, adaptive stratified design, stratified adaptive sampling, adaptive allocation stratified sampling	interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
Příbuzné	6	5
Shrnutí	Adaptive stratified sampling divides the population into strata and then applies an adaptive rule within each stratum: whenever an initially selected unit satisfies a pre-specified condition (e.g., a rare species is found, a variable exceeds a threshold), neighboring or related units are added to the sample. This combines the variance-reduction power of stratification with the ability to concentrate sampling effort where the phenomenon of interest is actually present.	Systematic sampling is a probability sampling technique in which every k-th element is selected from an ordered list of the population after a random starting point. With population size N and desired sample size n, the sampling interval k = N/n is computed and one unit is chosen at random from the first interval; all subsequent units are selected by adding k repeatedly. The method is operationally simple, yields a spread-out sample, and often achieves lower variance than simple random sampling when the list has no harmful periodicity.