Search results for "Application Notes"
showing 2 items of 2 documents
Migration and students' performance: detecting geographical differences following a curves clustering approach
2020
Students’ migration mobility is the new form of migration: students migrate to improve their skills and become more valued for the job market. The data regard the migration of Italian Bachelors who enrolled at Master Degree level, moving typically from poor to rich areas. This paper investigates the migration and other possible determinants on the Master Degree students’ performance. The Clustering of Effects approach for Quantile Regression Coefficients Modelling has been used to cluster the effects of some variables on the students’ performance for three Italian macro-areas. Results show evidence of similarity between Southern and Centre students, with respect to the Northern ones.
A model-based approach to Spotify data analysis: a Beta GLMM
2020
Digital music distribution is increasingly powered by automated mechanisms that continuously capture, sort and analyze large amounts of Web-based data. This paper deals with the management of songs audio features from a statistical point of view. In particular, it explores the data catching mechanisms enabled by Spotify Web API and suggests statistical tools for the analysis of these data. Special attention is devoted to songs popularity and a Beta model, including random effects, is proposed in order to give the first answer to questions like: which are the determinants of popularity? The identification of a model able to describe this relationship, the determination within the set of char…