LAB: TECHNIQUES OF DATA ANALYSIS

Quantitative data analysis has become increasingly important in the social sciences and the study of public policy. The use of these analyses (e.g. opinion polls, aggregate analysis of electoral data, evaluation of public policies) is now crucial in the field of academic research and in the activities of public institutions, think tanks and media. The ability to adequately understand and critically evaluate the results of quantitative analyses have therefore become necessary resources for any social scientist as well as for any professional in the job market. This lab introduces students to quantitative data analysis with the aim of providing a solid conceptual and operational basis through which to critically read the data and apply simple statistical models.

No formal prerequisite is required to participate. A basic knowledge of descriptive statistics can help, but it is not strictly necessary.

Knowledge and understanding At the end of the course the participants will be able to critically analyse quantitative data and to employ the main techniques of data analysis. The level of mathematical formalization (use of complex formulas and calculations) will be reduced. Students will instead be required to be able to assess the main methodological complexities inherent in data analysis and to use the most appropriate empirical tools in order to answer research questions in political science and public policy. Applying knowledge and understanding The course will provide students with the tools necessary to independently apply the main techniques of quantitative data analysis through the use of specialised statistical software. Making judgements The laboratory aims to provide students with the tools to effectively evaluate and use the main techniques of quantitative data analysis. Furthermore, the course aims to stimulate the ability to read and interpret evaluations of public policies through the use of statistical analysis. To this end, the course combines introductory lectures with laboratory sessions, group work and expert testimonials. Communication skills One of the main objectives of the laboratory is to provide students with the necessary skills to communicate the results obtained from quantitative analysis in an appropriate and effective way. Learning skills The laboratory will be conducted mainly in seminar/workshop form. The activities will therefore be characterized by a practical and dynamic approach, in order to favor the development of technical skills that can be used both in the job market and in the academic career.

The lab will provide students with the necessary skills to use the main statistical techniques employed in the social sciences. Alongside the main descriptive techniques (central tendency and dispersion measures), the course will introduce simple bivariate analysis (cross-tabulation and correlation), clarifying the concepts of control variable and spurious relationship. Students will subsequently be introduced to the concepts of inference and statistical significance. Finally, the laboratory will focus on linear regression analysis, which is the foundation of more sophisticated statistical techniques. During the course, basic elements for the evaluation of public policies will also be introduced, in particular with a counterfactual approach. The course will have a predominantly practical orientation: students will be required not only to understand the main data analysis techniques, but also and most importantly to put them into practice through the use of specialized statistical software. Each session will be based on an introduction of the techniques, followed by lab sessions in which students will be asked to independently carry out quantitative analyses and examine scientific papers.

Suggested readings Corbetta, P. (2014). Metodologia e tecniche della ricerca sociale, Il Mulino (Only the following chapters: Chapter III (La traduzione empirica della teoria), Chapter IV (Causalità ed esperimento), Chapter XIII (L’analisi monovariata), Chapter XIV (L’analisi bivariata)). Il Mulino Martini, A., Sisti, M. (2009). Valutare il successo delle politiche pubbliche. Il Mulino Other papers will be distributed by the instructors

Seminar-style classes Lab sessions

The assessment of student will take place through: 1) weekly written tests (in class and at home, individually and in group); 2) Final written exam. The weekly tests include short exercises on the topics covered during the week. Each exercise will have the same weight for evaluation purposes. Weekly tests will be graded through pass/fail assessment. The weekly tests weigh 50% on the final assessment. The final written exam (duration: 1 hour and 30 minutes) consists of a series of excercises concerning all the topics covered throughout the course. Each exercise will have the same weight for evaluation purposes. The final exam will be graded through pass/fail assessment. The final exam weighs 50% on the final assessment. Both in the weekly tests and in the final exam, students will be assessed based on their knowledge of the main data analysis tools; their ability to carry out basic statistical analyses independently; their ability to interpret and problematise the data; their ability to critically read a scientific article. The final grade (which will be pass/fail) is given by the average between the weekly tests and the written exam.

The criteria for assigning the thesis are: Exam grade Quality of the research project The project must be presented in written form (one page) introducing the main research question to be addressed and presenting a list of bibliographic references and a tentative index.

No