Search results for "Anàlisi multivariable"
showing 3 items of 3 documents
Bayesian classification for dating archaeological sites via projectile points
2021
Dating is a key element for archaeologists. We propose a Bayesian approach to provide chronology to sites that have neither radiocarbon dating nor clear stratigraphy and whose only information comes from lithic arrowheads. This classifier is based on the Dirichlet-multinomial inferential process and posterior predictive distributions. The procedure is applied to predict the period of a set of undated sites located in the east of the Iberian Peninsula during the IVth and IIIrd millennium cal. BC.
Studying students ́satisfaction at music schools in the Valencian Region
2017
[EN] Satisfaction is a key construct but complex to be measured. Within the cultural context and from the discipline of marketing, satisfaction consists of assessing some experiences without considering consumers ́ expectations. From this approach, this paper deals with an empirical research aiming at analyzing satisfaction among students of music conservatoires and schools. The research, qualitative and quantitative in nature, allowed to know users ́ assessment of different variables: studies, teaching staff, information technologies, premises and administration procedures. To do so, a self-administered survey was conducted using a structured questionnaire. Univariate and multivariate anal…
Multivariate Exploratory Comparative Analysis of LaLiga Teams: Principal Component Analysis
2021
The use of principal component analysis (PCA) provides information about the main characteristics of teams, based on a set of indicators, instead of displaying individualized information for each of these indicators. In this work we have considered reducing an extensive data matrix to improve interpretation, using PCA. Subsequently, with new components and with multiple linear regression, we have carried out a comparative analysis between the best and bottom teams of LaLiga. The sample consisted of the matches corresponding to the 2015/16, 2016/17 and 2017/18 seasons. The results showed that the best teams were characterized and differentiated from bottom teams in the realization of a great…