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Klastrianalüüs×Eksploratiivne faktorianalüüs (EFA)×
ValdkondStatistikaStatistika
PerekondLatent structureLatent structure
Tekkeaasta1939–1967
LoojaRobert C. Tryon (early development); Ward (1963) for hierarchical; MacQueen (1967) for k-means
TüüpUnsupervised classification / groupingLatent variable / dimension reduction
AlgallikasEveritt, B. S., Landau, S., Leese, M. & Stahl, D. (2011). Cluster Analysis (5th ed.). Wiley. ISBN: 978-0470749913Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗
Rööpnimetusedclustering, unsupervised classification, data clustering, numerical taxonomycommon factor analysis, açımlayıcı faktör analizi, factor analysis
Seotud54
KokkuvõteCluster analysis is a family of unsupervised multivariate techniques that partition a set of objects or observations into internally homogeneous, mutually distinct groups — clusters — based on measured characteristics, without any prior knowledge of group membership. It is widely used in market segmentation, bioinformatics, psychology, and social science to reveal natural groupings in data.Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance.
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ScholarGateVõrdle meetodeid: Cluster Analysis · EFA. Loetud 2026-06-15 aadressilt https://scholargate.app/et/compare