Journal article Open Access

Sex Determination in Forensic Dentistry Using Supervised Classification Techniques

Álvarez-Vaz, Ram\ń; Sassi, Carlos

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        <foaf:name>Álvarez-Vaz, Ram\ń</foaf:name>
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        <foaf:name>Sassi, Carlos</foaf:name>
    <dct:title>Sex Determination in Forensic Dentistry Using Supervised Classification Techniques</dct:title>
    <dct:issued rdf:datatype="">2020</dct:issued>
    <dct:issued rdf:datatype="">2020-01-01</dct:issued>
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    <dct:description>This article presents the main results obtained by characterizing the construction of students' satisfaction at Facultad de Ciencias Económicas y de Administración, Universidad de la República, Uruguay, through the use and comparison of two multivariate data analysis techniques: latent classes analysis and cluster analysis. The used data arise survey applied to a sample of undergraduate students of the Faculty, in the year 2009. This survey, present a structure in blocks: on the one hand, the variables that allow making a sociodemographic characterization of students. On the other hand (second block) there is the ECSI model (European Customer Satisfaction Index), which will be used to students' satisfaction characterization. The ECSI's variables are grouped in: expectations of the incoming students, the image that students have about the college, teaching and services quality, the needs and personal desires about college, and the perceived value. The main results presented in this work consider, on the one hand, that there is indeed a variable that refers to students' satisfaction and that it is defined by four latent classes, from the interaction of the 6 manifest variables. On the other hand, from the analysis of clustering through the Ward method, it is proposed to group the students into three clusters. Finally, the results' comparison obtained with both techniques it is also presented.</dct:description>
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