Linganisha mbinu

	Adaptive Simple Random Sampling	Sampuli ya Kisistemati
Nyanja	Metodolojia ya Dodoso	Metodolojia ya Dodoso
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1990–1992	Mid-20th century (Cochran 1953; Kish 1965)
Mwanzilishi	Steven K. Thompson	William G. Cochran; formalized in survey sampling theory
Aina	Probability-based adaptive sampling design	Probability sampling design
Chanzo asilia	Thompson, S. K. (1992). Sampling. John Wiley & Sons. ISBN: 978-0471548850	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Majina mbadala	ASRS, adaptive SRS, adaptive random sampling, sequential adaptive sampling	interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
Zinazohusiana	5	5
Muhtasari	Adaptive simple random sampling (ASRS) begins with a conventional simple random sample and then expands the sample in regions where the variable of interest exceeds a pre-specified threshold. Units neighboring a qualifying observation are added to the sample, allowing the design to concentrate effort where the population is dense or rare, while retaining unbiased estimation through the Horvitz-Thompson or Hansen-Hurwitz estimators. The approach was systematized by Steven K. Thompson in the early 1990s as part of the broader adaptive sampling framework.	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.