Σύγκριση μεθόδων

	Δειγματοληψία Πολλαπλών Σταδίων	Στρωματοποιημένη Δειγματοληψία
Πεδίο	Μεθοδολογία Επισκοπήσεων	Μεθοδολογία Επισκοπήσεων
Οικογένεια	Process / pipeline	Process / pipeline
Έτος προέλευσης	1950s–1960s (formalized in Kish 1965 and Cochran 1977)	1977
Δημιουργός	Leslie Kish; William G. Cochran	William G. Cochran
Τύπος	Probability sampling design	Probability-based survey sampling design
Θεμελιώδης πηγή	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0-471-16240-7
Εναλλακτικές ονομασίες	multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling	Proportional Stratified Sampling, Optimal Allocation Sampling, Stratum-Based Sampling, Tabakalı Örnekleme
Συναφείς	5	2
Σύνοψη	Multistage sampling is a probability-based design that selects a sample by working through two or more successive levels of a population hierarchy — for example, first selecting regions, then districts within those regions, then households within those districts. It makes large-scale surveys practical when a complete population list is unavailable or when the population is geographically dispersed, by concentrating fieldwork within a manageable number of sampled units at each stage.	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.