Journal article Open Access

# Sex Determination in Forensic Dentistry Using Supervised Classification Techniques

Álvarez-Vaz, Ram\ń; Sassi, Carlos

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{
"publisher": "Zenodo",
"DOI": "10.5281/zenodo.3677593",
"title": "Sex Determination in Forensic Dentistry Using Supervised Classification Techniques",
"issued": {
"date-parts": [
[
2020,
1,
1
]
]
},
"abstract": "This article presents the main results obtained by characterizing the\nconstruction of students' satisfaction at Facultad de Ciencias\nEcon\u00f3micas y de Administraci\u00f3n, Universidad de la Rep\u00fablica,\nUruguay, through the use and comparison of two multivariate data\nanalysis techniques: latent classes analysis and cluster analysis. The\nused data arise survey applied to a sample of undergraduate students\nof the Faculty, in the year 2009. This survey, present a structure in\nblocks: on the one hand, the variables that allow making a\nsociodemographic characterization of students. On the other hand\n(second block) there is the ECSI model (European Customer\nSatisfaction Index), which will be used to students' satisfaction\ncharacterization. The ECSI's variables are grouped in: expectations of\nthe incoming students, the image that students have about the college,\nteaching and services quality, the needs and personal desires about\ncollege, and the perceived value. The main results presented in this\nwork consider, on the one hand, that there is indeed a variable that\nrefers to students' satisfaction and that it is defined by four latent\nclasses, from the interaction of the 6 manifest variables. On the other\nhand, from the analysis of clustering through the Ward method, it is\nproposed to group the students into three clusters. Finally, the results'\ncomparison obtained with both techniques it is also presented.",
"author": [
{
"family": "\u00c1lvarez-Vaz, Ram\\\u0144"
},
{
"family": "Sassi, Carlos"
}
],
"type": "article-journal",
"id": "3677593"
}
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