Matilde Bini – författare

Data Science today represents a broad domain of knowledge development from data, where statistical and data analysis methods can make an important contribution in the different domains where data management and processing are required.

This book contains a selection of the improved contributions submitted by participants at the conference of the Italian Statistical Society - SIS 2022 held in Caserta 22-24 June 2022. The scientific community of Italian statistics, which gathers around the SIS, is paying particular attention to the development of statistical techniques increasingly oriented toward the processing of large data, mainly, of complex data.  The main goal is to provide the analysis of the data and the interpretability of the obtained results, with a view to decision support and the reliability of the data outcomes. The aim of this volume is to show some of the most relevant contributions of statistical and data analysis methods in preserving the quality of the information to be processed, especially when it comes from different, often non-official sources; as well as in the extraction of knowledge from complex data (textual, network, unstructured and multivalue) and in the explicability of results. Data Science today represents a broad domain of knowledge development from data, where statistical and data analysis methods can make an important contribution in the different domains where data management and processing are required. This volume is addressed to researchers but also to Ph.D. and MSc students in the field of Statistics and Data Science to acquaint them with some of the most recent developments towards which statistical research is orienting, in prevalence in Italy.

The book presents statistical methods and models that can usefully support the ev- uation of educational services and quality of products. The contributions collected in this book summarize the work of several researchers from the universities of Bologna, Firenze, Napoli and Padova. The contributions are written with a cons- tent notation and a uni?ed view, and concern methodological advances developed mostly with reference to speci?c problems of evaluation using real data sets. The evaluation of educational services, as well as the analysis of judgements and preferences, poses severe methodological challenges because of the presence of one or more of the following aspects: the observational (non experimental) nature of the context, which is associated with the well-known problems of selection bias and presence of nuisance factors; the hierarchical structure of the data, that entails c- related observations and consideration of effects at different levels of the hierarchy and their interactions (multilevel analysis); the multivariate and qualitative nature of the dependent variable, that requires the use of ad hoc statistical methodologies; the presence of non observable factors, e. g. the satisfaction, calling for the use of latent variables models; the simultaneous presence of components of pleasure and components of uncertainty in the explication of the judgments, that asks for the speci?cation and estimation of mixture models. The ?rst part of the book deals with latent variable models.

The book presents statistical methods and models that can usefully support the ev- uation of educational services and quality of products. The contributions collected in this book summarize the work of several researchers from the universities of Bologna, Firenze, Napoli and Padova. The contributions are written with a cons- tent notation and a uni?ed view, and concern methodological advances developed mostly with reference to speci?c problems of evaluation using real data sets. The evaluation of educational services, as well as the analysis of judgements and preferences, poses severe methodological challenges because of the presence of one or more of the following aspects: the observational (non experimental) nature of the context, which is associated with the well-known problems of selection bias and presence of nuisance factors; the hierarchical structure of the data, that entails c- related observations and consideration of effects at different levels of the hierarchy and their interactions (multilevel analysis); the multivariate and qualitative nature of the dependent variable, that requires the use of ad hoc statistical methodologies; the presence of non observable factors, e. g. the satisfaction, calling for the use of latent variables models; the simultaneous presence of components of pleasure and components of uncertainty in the explication of the judgments, that asks for the speci?cation and estimation of mixture models. The ?rst part of the book deals with latent variable models.