Data Science

Programme The course is composed by the following main sections, organized in modules. -Section I. INTRODUCTION 1) A three-dimensional framework for a quantitative approach to the economic analysis and management. -Section II. DATA 2) Nature, collection, semantic modelling, and analysis of big data and little data within organizations and socio-economic systems. 3) Classification systems and information taxonomies for the management of organizations and socio-economic systems. -Section III. TOOLS Quantitative tools for economic modelling and management 4) Cost Benefit Analysis 5) Regression Methods for Continuous and Discrete Responses from Parametric to Nonparametric Approaches 6) Productivity and Efficiency Analysis: main techniques in an unified approach from parametric to nonparametric models. 7) Statistical Tools from the Physics of Complex Systems. 8) Sensitivity Analysis and Sensitivity Auditing techniques. -Section IV. APPLICATIONS 9) Available data sources for empirical analysis in economics and management 10) Applications in economics and management, including public sector services. Part one. Outline of the existing literature. 11) Applications in economics and management, including public sector services. Part two. Developments during the Project work activities (see below). Group project works The group project works will be defined according to the interest of students. The following broad projects areas will be available: 1) Estimation of socio-economic models using ISTAT (http://www.istat.it/it/prodotti/banche-dati) and EUROSTAT (http://ec.europa.eu/eurostat) data; 2) Empirical analysis of education, science and technology systems, with data coming from ongoing European research projects, including the ETER project (http://eter.joanneum.at/imdas-eter/ ); 3) Application of statistical tools from the physics of complex systems to compare the scientific performance of countries, and case studies in collaboration with the Italian Institute of Technology (https://www.iit.it/it/home.html, http://lns.iit.it/ ); 4) Applications of sensitivity analysis and sensitivity auditing, in collaboration with the Joint Research Center of the European Commission, Ispra (https://ec.europa.eu/jrc/ ). Detailed guidelines on how to make a presentation, how to make a bibliographic search, and on how to carry out the project work and on the choice of the technique to carry out the analysis will be provided during the practical laboratory sessions.

No prerequisites requested.

Materials A base of the course is the material contained in: Daraio C. (2016) Eds., Challenges of Big Data for Economic Modeling and Management: Tools from Efficiency Analysis, Sensitivity Analysis, Sensitivity Auditing and Physics of Complex Systems. Proceedings of the Workshop of the 10-11 November 2015, DIAG Sapienza University of Rome, Edizioni Efesto, Rome. During the course, the Lecture Notes and additional materials will be distributed.

Classes will be held mainly in-person. Lectures, tutorials and face-to-face laboratory will be supplemented by online seminars conducted by experts.

Evaluation All the course, and in particular the group project work activities, will require the active participation of students that will be asked to make small homework assignments, an in-class presentation and to prepare a group project work with real data according to their interest. The course grade determination, as a consequence, is as follows. Homework assignments and in-class presentation: around 30-40%. Final project work realization, presentation and discussion: around 60-70%.

Materials A base of the course is the material contained in: Daraio C. (2016) Eds., Challenges of Big Data for Economic Modeling and Management: Tools from Efficiency Analysis, Sensitivity Analysis, Sensitivity Auditing and Physics of Complex Systems. Proceedings of the Workshop of the 10-11 November 2015, DIAG Sapienza University of Rome, Edizioni Efesto, Rome. During the course the Lecture Notes and additional materials will be distributed.

The course will be conducted in the traditional mode, that is, in-person. It will be possible to have some seminars with experts and lecturers online.