If you haven’t enrolled yet, please look at code 6810.
If you have already enrolled, the course code is available in Studenti Online.
6810 - Statistical Sciences
The objective of the Second cycle degree programmes in Statistical Sciences is to train experts specialised in the management, analysis and interpretation of data, in order to produce information that supports the decision-making processes of public and private entities.
The Degree Programme represents a natural continuation of first-cycle degrees in statistical disciplines or a methodological path for graduates holding other first-cycle degrees with an adequate theoretical knowledge of mathematics and statistics (especially Mathematics, Computer Science, Economics).
The Degree Programme Catalogue is organized to enable graduates to obtain:
- sound knowledge of the statistical methodology for collecting, processing and modelling data, including big data;
- adequate knowledge of the statistical and IT techniques used to support the strategic and operational decisions of firms;
- sound skills in the multivariate statistical inference and analysis methods used in biostatistics by research institutions and public bodies responsible for the production of official statistics;
- good skills in the analysis, interpretation and communication of results.
The Degree Programme comprises curricula that differ principally by area of specialisation and by the professional roles for which training is given. The different paths provide the methodological and IT tools for training experts able to formalise, analyse and solve complex problems under conditions of uncertainty; the acquisition of sound methodological skills and the specific social and bio-demographic knowledge needed to study, monitor and predict demographic and health-related phenomena relating to populations and analyse the problems associated with the management and production of official statistics, in order to work for the institutions responsible for official statistics at national and international level.
The curricula all have common core activities focused on the quantitative preparation of graduates. The first year principally focuses on the statistical methodology relating to probability, the theory of statistical inference and statistical models, and certain IT skills needed for data collection and processing. During the second year, IT skills for data analysis, multivariate analysis methodologies, models and methods for demographic, social and biostatistical analysis, and tools for the analysis and production of official statistics are covered, at different levels of depth depending on the curriculum.
The learning objectives are reached via the advanced organisation of teaching activities, combining theoretical analysis with practical applications of the concepts learned in laboratory sessions, which are based on the use of statistical and IT software in order to develop, study and analyse specific cases, both real and simulated.
The learning process may be completed by a curricular internship that enables the knowledge acquired to be put into practice.
