Analysis of two-step clusters with SPSS

Authors

DOI:

https://doi.org/10.1344/reire2017.10.11017

Keywords:

Classification, Conglomerate, Two-step cluster.

Abstract

The method of cluster analysis in two phases, also called two-step cluster analysis, is an exploratory tool designed to reveal natural groupings of a data set, in order to generate information criteria, cluster frequencies, and descriptive statistics by cluster as well as bar and sector charts, and graphs showing the relevance of variables. The method of two-step cluster analysis has unique features compared to other methods of traditional clustering, including: an automatic procedure for calculating the optimal number of clusters, the ability to create models of clusters with both categorical and continuous variables, and the possibility of working with large data files.

References

Contreras Higuera, W. E., Martínez Olmo, F., Rubio Hurtado, M. J., y Vilà Baños, R. (2016). University students perceptions of e-portfolios and rubrics as combined assessment tools in education courses. Journal of Educational Computing Research, 54(1), 85-107. doi:10.1177/0735633115612784

Kaufman, L., y Rousseeuw, P. J. (1990). Finding groups in data. An introduction to cluster analysis. New York: John Wiley & Sons. doi:10.1002/9780470316801

Pérez, C. (2011). Técnicas de segmentación. Conceptos, herramientas y aplicaciones. Madrid: Gaceta Grupo Editorial.

Vilà Baños, R., Rubio Hurtado, M. J., Berlanga Silvente, V., y Torrado Fonseca, M. (2014). Cómo aplicar un clúster jerárquico en SPSS. Revista d’Innovació i Recerca en Educació, 7(1), 113-127. doi:10.1344/reire2014.7.1717

Published

2016-11-15

How to Cite

Rubio-Hurtado, M.-J., & Vilà Baños, R. (2016). Analysis of two-step clusters with SPSS. REIRE Revista d’Innovació I Recerca En Educació, 10(1), 118–126. https://doi.org/10.1344/reire2017.10.11017

Issue

Section

Methodological articles

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