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Enkel tilfeldig utvalg på nett×Systematisk utvalg×
FagfeltSurveymetodikkSurveymetodikk
FamilieProcess / pipelineProcess / pipeline
OpprinnelsesårLate 1990s–2000s (digital adaptation)Mid-20th century (Cochran 1953; Kish 1965)
OpphavspersonAdapted from classical simple random sampling (Neyman, 1934) for web/digital survey contexts; operationalised by survey methodology researchers from the late 1990s onwardWilliam G. Cochran; formalized in survey sampling theory
TypeProbability sampling designProbability sampling design
Opprinnelig kildeCouper, M. P. (2008). Designing Effective Web Surveys. Cambridge University Press. ISBN: 978-0521700535Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Aliasweb simple random sampling, internet SRS, digital random sampling, online SRSinterval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
Relaterte55
SammendragOnline simple random sampling applies the logic of classical simple random sampling (SRS) to digital data collection: every member of a defined online population has an equal and independent probability of being selected, and the survey is administered via web platform, email link, or online panel. The approach combines the statistical rigour of probability sampling with the speed and cost advantages of internet-based survey delivery.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.
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ScholarGateSammenlign metoder: Online simple random sampling · Systematic Sampling. Hentet 2026-06-15 fra https://scholargate.app/no/compare