To develop skills to identify a relevant research question on social phenomena, to elaborate an appropriate research design and to correctly understand and evaluate the results of quantitative statistical analysis has become an essential ability for social scientists. This course is aimed to provide an introduction to the methods of research in social sciences and the foundations of the main methods of empirical analysis for the study and research on issues in the field of international relations. In addition to the theoretical lectures, practices dealing with real world examples and the use of statistical packages (R, R-studio) are also provided in order to allow students to improve abilities in collecting, analysing, interpreting and presenting data and empirical findings. the course aims at providing the students the main tools to: i) perform data analysis using descriptive and inferential statistics; ii) compare and contrast different approaches to the empirical analysis and select the most appropriate methodology in the light of the available statistical information and the objective of the study; iii) make informed decisions on selecting the appropriate techniques for describing and presenting the data.

Knowledge and understanding: the participants are expected to identify puzzling research questions on timely relevant issues and to identify the appropriate methodology to address that research question empirically. They will acquire knowledge on the main qualitative research methods and a solid knowledge of the main statistical methods for data analysis and the ability to carry out empirical investigations on the main topics (economic, social, political, demographic) of interest for the social scientists. With reference to statistical methodologies, the students are expected to improve their understanding of the methodological issues and develop the capacity to apply the techniques for: a) the descriptive analysis of data; b) the study of relations between variables from both a descriptive and an inferential perspective; c) a multivariate analysis of data. Students will also acquire skills on the use of several database structures and their management and processing using statistical software. Applying knowledge and understanding: Upon the end of the course, the students are expected to strengthen their methodological and analytical skills so that they are allowed to independently interpret analysis and empirical research on the most relevant areas of interest for an international political scientist (for example, demographic and political issues). The participants will be able to: i) evaluate the robustness of the main analytical findings and the reliability of the statistical methods used in the empirical investigation; detect possible inconsistencies in the empirical applications and consider the use of alternative approaches; ii) design case studies relevant for public policy, by outlining the topic of interest, selecting the databases, identifying the methodologies for the empirical analysis, communicating the main results achieved in the form of presentations or reports. Making judgements: the course is aimed at promoting a critical approach on the use of several methods of data analysis for the study of the international subjects of interest. The participants are expected to: i) develop critical skills on the use of the various methods depending on the objectives of the analysis; ii) be able to evaluate the specific contribution of each methodology of data analysis; iii) develop the ability to consistently include the contribution provided by the empirical studies within a broader approach that includes the interdisciplinary background of the students. Communication skills: the students will learn to communicate univocally and clearly the approach adopted for the empirical study, with particular reference to the structure of the databases, the statistical methods used, the results achieved. Effective communication skills of the empirical results and the capacity of an appropriate technical language will be achieved through written tests, presentation and discussion of empirical research, scientific articles and reports issued by international institutions. Learning skills: the instructional methods adopted in this course include case studies, seminars other than the use of learning verification methods through peer evaluations. All of these activities will contribute to improve the capacity of independent judgment and the development of self-learning skills by the students. These abilities will be achieved through the analysis of statistical methods applied to economic, political and social sciences. An important objective of this course is to ensure that students will use quantitative methods in subsequent professional or academic activities (laboratories, stages, traineeships).

Introduction to Statistical Methodology. International and national sources of data for the analysis of economic, social, political and demographic phenomena. Descriptive statistics: describing real data with tables and graphs; measures of positions, variability and shapes. Analysis of concentration. Interpretation and comparison of data referring to socio-economic phenomena: simple and complex (synthetic) index numbers. Probability distributions. Statistical inference: point estimation, confidence interval and hypothesis testing. Association between categorical variables. Linear regression and correlation. Multiple regression and correlation. Regressions with categorical and quantitative predictors. Introduction to logistic regression. Elements of multivariate statistical analysis: principal component analysis and hierarchical and non-hierarchical cluster analysis. Data management and processing using R and R-Studio software. Case studies and applied exercises based on real data, measures and indicators used for the analysis of topics related to the course (as an example, data and analysis related to the Human Development Index, Sustainable Development Goals, the World Bank Development Indicators, European Regional Competitiveness Index and based on Eurostat, OECD, IMF and UNSD datasets).

Newbold, P., Carlson, W. L., & Thorne, B. M. (2013). Statistics for business and economics. Pearson (the detailed program of the course reports book chapters and paragraphs to study). Corbetta, P. (2003). Social research: Theory, methods and techniques. Sage. (the detailed program of the course reports book chapters and paragraphs to study). Additional chapters/research articles provided by the instructors Teacher/class notes (in the detailed program an asterisk (*) indicates the topics for which the learning materials will be provided by the teacher)

Lectures, exercises, Lab with R and R-studio, applied exercises, interactive learning through published data, measures and report visualizations, case studies in social sciences based on real data, also using statistical and econometric packages and advanced spreadsheet.

30% written midterm exam using R 70% oral final exam on the remaining content of the course

The thesis should be a work in which methods learned throughout the course are applied to political, economic or social phenomena. The topic is agreed with the teacher.