The objective of the Second cycle degreeprogrammes in Statistical Sciences is to train experts specialised in themanagement, analysis and interpretation of data, in order to produceinformation that supports the decision-making processes of public and privateentities.
The Degree Programme represents a naturalcontinuation of first-cycle degrees in statistical disciplines or amethodological path for graduates holding other first-cycle degrees with anadequate theoretical knowledge of mathematics and statistics (especiallyMathematics, Computer Science, Economics).
The Degree Programme Catalogue is organisedto enable graduates to obtain:
- sound knowledge of the statisticalmethodology for collecting, processing and modelling data, including big data;
- adequate knowledge of the statistical andIT techniques used to support the strategic and operational decisions of firms;
- sound skills in the multi-variatestatistical inference and analysis methods used in biostatistics by researchinstitutions and public bodies responsible for the production of officialstatistics;
- good skills in the analysis,interpretation and communication of results.
The Degree Programme comprises curriculathat differ principally by area of specialisation and by the professional rolesfor which training is given. The different paths provide the methodological andIT tools for training experts able to formalise, analyse and solve complexproblems under conditions of uncertainty; the acquisition of soundmethodological skills and the specific social and bio-demographic knowledgeneeded to study, monitor and predict demographic and health-related phenomenarelating to populations and analyse the problems associated with the managementand production of official statistics, in order to work for the institutionsresponsible for official statistics at national and international level.
The curricula all have common coreactivities focused on the quantitative preparation of graduates. The first yearprincipally focuses on the statistical methodology relating to probability, thetheory of statistical inference and statistical models, and the IT skillsneeded for the collection and processing of data. The second year examines thetechniques of multi-variate analysis and strategies for the analysis ofqualitative data. The programme is supplemented by courses on samplingtechniques, non-parametric inference, demographics, biostatistics and methodsfor the production and analysis of official statistics that are tailored to thechosen curriculum.
The learning objectives are reached via theadvanced organisation of teaching activities, combining theoretical analysiswith 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 acurricular internship that enables the knowledge acquired to be put intopractice.
