Argomenti dell'insegnamento
1. Data Management Fundamentals, 2. Descriptive Statistics, 3. Data handling and visualisation with R, 4. Exploratory Statistical Analysis of Cross-sectional, Time Series Data, and (possibly) Survey Data with R.

Modalità di insegnamento
Lectures and exercises

Obiettivi formativi
ILO (Intended Learning Outcomes) Introduction to Data Management and Data Analysis ILO1 Knowledge and understanding ILO1.2 The student acquires knowledge of economic theory necessary to understand and analyse economic and business phenomena in the public sector in order to support decision-making processes. Knowledge of public policy and the tools necessary for the design of sustainable policies will be consolidated. Knowledge related to the labour market, education and health will also be deepened, functional to the development of public policy analysis and evaluation skills. ILO2 Ability to apply knowledge and understanding ILO2.4 ability to interpret results deriving from statistical and econometric analysis in contexts of interest to companies and public bodies ILO3 Making judgements ILO3.1 ability to apply acquired knowledge to interpret economic and business phenomena in order to make managerial and operational decisions in the context of public administration ILO3.2 ability to select data and use appropriate information to describe a problem concerning the design, implementation and evaluation of public sector projects and policies, aiming at innovation and improvement of processes, products and results ILO3.3 ability to relate models and empirical evidence in the study of public policy phenomena ILO4 Communication skills ILO4.1 ability to communicate effectively in oral and written form the specialised contents of the individual disciplines, using different registers according to recipients and communicative and didactic purposes, as well as to evaluate the formative effects of his/her communication ILO5 Learning ability ILO5.1 ability to use information technology autonomously to carry out bibliographical research and investigations and for one's own training and further education.

Obiettivi formativi e risultati di apprendimento (ulteriori info.)
Knowledge and understanding of different types of data and their representation. Applying different statistical descriptions based on the data type. Ability to interpret (exploratory) analysis results in the context of public policy.

Modalità d'esame
Written exam with theoretical questions, problem-solving exercises, and interpretation of analysis results. Voluntary midterm, subject to timetable constraints, (ILOs 1-5) and obligatory final exam (ILOs 1-5), both written. The midterm exam covers the first half of the course materials (data management fundamentals), while the final exam covers either the second half of the course, or the entire course. The final grade will be a weighted average of the midterm exam (50%) and the final exam (50%). Students who do not take the midterm or who reject their midterm grade will be required to take a longer final exam, which will count for 100% of the final grade.

Criteri di valutazione
Criteria for the exam: correctness and clarity of answers, knowledge and understanding of statistical methods, ability to interpret outputs and to correctly use formal code. Students will be evaluated on their understanding and ability to apply data management, visualisation, and analysis techniques (correct procedures, accurate solutions, and clarity of answers are essential); knowledge and understanding of descriptive statistical methods; ability to interpret code and outputs.

Bibliografia obbligatoria

Lecture notes.

Additional materials and references will be provided by the lectures throughout the course.

Bibliografia facoltativa

• Statistical Methods in Public Policy Research, Heiss A. (2025)
• Healy, K. (2018). Data visualization: A practical introduction. Princeton University Press.
• Data Visualization with R OSDC MiniSeries: Reproducible Research (available here).
• Stock, James H. and Mark W. Watson. Introduction to Econometrics. Pearson, 2014

Altre informazioni
The Preparatory Course in Statistics is warmly suggested.