Linganisha mbinu

	Sampuli ya Nguzo za Mtandaoni	Upimaji wa Kisayansi mtandaoni
Nyanja	Metodolojia ya Dodoso	Metodolojia ya Dodoso
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	Late 1990s–2000s (as internet surveys became prevalent)	Late 1990s–2000s (web survey era)
Mwanzilishi	Adapted from cluster sampling (Mahalanobis, Hansen & Hurwitz, 1940s) to online survey contexts	Adapted from classical systematic sampling (Madow & Madow, 1944) for web survey contexts
Aina	Probability sampling technique	Probability sampling design
Chanzo asilia	Couper, M. P. (2000). Web surveys: A review of issues and approaches. Public Opinion Quarterly, 64(4), 464–494.	Couper, M. P. (2008). Designing Effective Web Surveys. Cambridge University Press. ISBN: 978-0521713528
Majina mbadala	internet cluster sampling, web cluster sampling, digital cluster sampling	web systematic sampling, digital systematic sampling, interval sampling online, e-survey systematic sampling
Zinazohusiana	4	4
Muhtasari	Online cluster sampling applies the classic cluster sampling logic to internet-based research: naturally occurring digital groups — such as online communities, email lists, forum memberships, or institutional user registries — serve as clusters, and selected clusters are surveyed in full or partially via web-based instruments. It offers a practical route to probability-based online samples when no complete list of individuals exists but lists of digital groups are accessible.	Online systematic sampling applies the classical every-k-th-element rule to digital survey contexts — selecting respondents from a web panel, membership database, or visitor stream at a fixed interval. It combines the operational simplicity of systematic sampling with the reach and speed of online data collection, producing a roughly representative sample without requiring complex randomisation infrastructure.