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Svērta izlase×Sistemātiskā izlase×
NozareAptauju metodoloģijaAptauju metodoloģija
SaimeProcess / pipelineProcess / pipeline
Izcelsmes gads1940s–1952 (formalized in large-scale government survey work and the Horvitz-Thompson estimator)Mid-20th century (Cochran 1953; Kish 1965)
AutorsMorris H. Hansen, William N. Hurwitz; D. G. Horvitz and D. J. Thompson (theoretical framework)William G. Cochran; formalized in survey sampling theory
TipsProbability sampling designProbability sampling design
PirmavotsCochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407
Citi nosaukumiprobability proportional to size sampling, PPS sampling, unequal probability sampling, importance samplinginterval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling
Saistītās65
KopsavilkumsWeighted sampling is a probability-based design in which units are selected with unequal probabilities proportional to a known auxiliary measure of size or importance. Sampling weights — the inverse of inclusion probabilities — are applied during analysis so that each sampled unit correctly represents the population units it stands for. The approach underpins large-scale government, health, and social surveys where simple random sampling would be inefficient.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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ScholarGateSalīdzināt metodes: Weighted Sampling · Systematic Sampling. Izgūts 2026-06-15 no https://scholargate.app/lv/compare