ANÁLISE DE CORRESPONDÊNCIAS MÚLTIPLAS VIA OPTIMAL SCALING APLICADA A VARIÁVEIS DO MEIO ESCOLAR RELATIVAS À ALUNOS DO ENSINO SECUNDÁRIO EM PORTUGAL - SILVA, Domingos José Lopes da; OLIVEIRA, Maria Manuela Melo (Brazilian Journal of Biometrics, 2017)
Multiple Correspondence Analysis (MCA) is a multivariate method that might be particularly useful in the analysis of a large set of qualitative data. Through MCA, it is possible to assess the relationship between large sets of variables and produce geometric maps to visualize potential interactions. Using optimal scaling procedure, this study aims to: a) investigate the motivation levels of high schools students for the disciplines of Portuguese, Mathematics and Physical Education; b) establish relationships between motivation levels and students’ characteristics (gender, course, grade and sports). It highlights the pioneering this application. By applying MCA, it was identified variables and categories of variables with close attributes, which further allowed the definition of relatively homogeneous subgroups. It was retained three dimensions. The dimension one refers to «sports practice», the dimension two is directed particularly to the “languages learning and humanities”, and the dimension three represents simultaneously the “physical dexterity and abstract reasoning”.