Resumen

MARTINEZ-NORIEGAS, Hugo Arnaldo; MEDRANO-BROCHE, Bolívar Ernesto; FERNANDEZ-CAPESTANY, Lytyet  y  TEJEDA-RODRIGUEZ, Yunier Emilio. Multivariate data analysis as decision making support in student selection in software projects. Ing. Ind. [online]. 2013, vol.34, n.2, pp.130-142. ISSN 1815-5936.

Personnel selection is a vital process that has a direct influence on the success of any organization. This paper aims to generate information for decision support in the selection of students for software projects. The multivariate data analysis techniques are applied to the data set of academic qualifications of Computer Science Engineering´s second year students. The principal component analysis is used in order to reduce the number of variables under study and based in the summarized information, it is utilized the cluster analysis to form 3 groups. Through the factor analysis, it was possible to identify 3 latent factors that act on different groups of subjects. The generated information is used as a support for the decision-making to develop strategies on the training job from production.

Palabras clave : principal component analysis; cluster analysis; factorial analysis; personnel selection.

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