Statistics, Economics, and Social Sciences

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Curriculum(s) for 2025 - Statistics, Economics, and Social Sciences (33505)

Single curriculum

1st year

Lesson	Semester	CFU	SSD	Language
97786 \| LINEAR ALGEBRA	1st	9	MAT/03	ITA
Educational objectives Learning goals Knowledge and comprehension of the basic concepts and techniques of linear algebra and of analytic geometry of the plane and the space and ability to apply them to the study and resolution of simple problems also in the context of other courses. Knowledge and understanding Good theoretical and practical knowledge of matrices, linear systems and other fundamental notions of linear algebra and ability to understand these issues also in the context of other courses. Applying knowledge and understanding Ability to use the acquired skills for solving simple problems on matrices, linear systems and other fundamental notions of linear algebra, also for their use required in other courses. Making judgements Good ability to recognize, frame and set out the resolution of simple problems on matrices, linear systems and other fundamental notions of linear algebra, possibly selecting appropriately among the methods learned. Communication skills Good presentation skills of basic concepts and techniques of linear algebra as well as solution methods to simple problems. Learning skills Good learning ability of mathematical issues in other courses, by virtue of the comprehension of the logical-deductive character of the discipline.
1010575 \| Statistics	1st	9	SECS-S/01	ITA
Educational objectives Learning goals. The primary objective is to provide students with basic concepts and procedures of descriptive statistics. At the end of the course the student must be able to design a small census survey and to conduct descriptive analyses of the data through the use of a statistical software. Knowledge and understanding. Upon completion of the course, students know and understand the main procedures of descriptive statistics. They are able to organize data in simple and contingency tables and to synthesize them through graphical representations. They know and are able to calculate the most important statistical indicators that measure (a) position, variability and form of simple distributions and (b) important aspects of the joint distribution of two variables. Furthermore, they have acquired the notion of statistical model and are able to implement a simple regression model. Applying knowledge and understanding. Upon completion of the course, students are able to apply the knowledge acquired, in order to interpret and critically evaluate the results of descriptive analysis. Making judgements. Through a large number of exercises on all the topics covered, students develop autonomous judgment skills that allow to identify the most appropriate methods to solve problems of descriptive statistics and to critically interpret the results of the elaborations provided by the software. Communication skills Students, through the study and the performance of practical exercises, acquire the technical-scientific language of the discipline, that must be properly used both in the written and in the oral examinations. Learning skills Students who pass the exam will have knowledge of the fundamental notions for the descriptive analysis of data. They will also be able to implement simple codes to organize data in tables and synthesize them through graphics and/or calculation of important indicators. Therefore, they have acquired the basics to learn what will be proposed in the subsequent statistical courses.
1017587 \| INFORMATICS	1st	9	INF/01	ITA
Educational objectives Learning goals. The primary objective is to learn how to describe simple processes in a formal way, through the definition of algorithms, and to acquire a methodology to evaluate the complexity of an algorithm. Students must be able to: - unambiguously define a problem, - identify precisely which data should be processed, - how to represent such data, - how to decompose a procedure in steps that solves the problem. These skills are expressed through the use of the Java programming language. Knowledge and understanding. After attending the course the students know and understand the concept of algorithm and how an algorithm can be expressed using a programming language. They use the basic constructs of the Java language and are aware of the possibility of solving the same problem with different computational complexity algorithms. They also know various algorithms for solving basic problems, such as searching and sorting, and some numerical algorithms. Applying knowledge and understanding. At the end of the course students are able to formalize algorithms for simple problems, implement them in Java language, passing through all phases: design, writing the source code, compilation, debugging and execution. They know the notations that allow to express asymptotically the complexity of an algorithm. They know how textual, numerical, and other information can be encoded. Making judgements. Students are able to appreciate the difference between solving a problem and formally describing a resolutive process. They manage to evaluate how different implementation choices can lead to solutions with different efficiency characteristics, applying paradigms studied in the context of basic problems. Through intense laboratory activities they acquire a greater awareness of the processes underlying the use of a computer. Communication skills. Students acquire the formal rigor necessary to use a programming language. They are able to appreciate and foresee the repercussions, in terms of complexity, of the application of different resolution techniques. They know how to apply decomposition techniques, in order to reduce the solution of complex problems to the solution of simpler problems. Learning skills. Students who pass the exam can analyze the structure of a program, even complex, can easily be productive using any other imperative or object-oriented programming language, can distinguish for which problems an automated solution may exist.
10612162 \| MATHEMATICAL ANALYSIS I COURSE	2nd	9	MAT/05	ITA
Educational objectives Knowledge and understanding. Good theoretical and practical knowledge of differential calculus, integration, power series (real functions of one real variable). Ability to understand these issues also in the context of other courses. Applying knowledge and understanding. Ability to use the acquired skills for solving simple problems and for their use required in other courses. Making judgements. Good ability to recognize, frame and set out the resolution of simple problems, selecting appropriately among the methods learned. Communication skills. Good presentation skills of basic concepts and techniques of Calculus. Learning skills. Good learning ability of mathematical issues in other courses, by virtue of the comprehension of the logical-deductive character of the discipline.
1017588 \| Political Economics I	2nd	9	SECS-P/01	ITA
Educational objectives Learning goals The aim of the course is to present the basic principles and tools of modern economic theory - both micro and macroeconomics - showing at the same time their empirical relevance. This is achieved by integrating the theoretical exposition with the description of actual features of the Italian economy and of other national economies. Knowledge and understanding The lectures aim at allowing students to gain a general knowledge of the essential concepts used in economic analysis and a historical perspective of the development of the main theoretical approaches to the study of the economic system. Applying knowledge and understanding Students will learn the main lines of development of microeconomic and macroeconomic theories, including monetary theory, and will have a general view of economic policy. Making judgements The course aims at fostering students' ability to apply economic theory and methodology to the analysis of economic facts and of economic policy. These analytical abilities will be such to be also applied to current phenomena. Communication skills Frontal teaching and preparation of oral examination allows students to acquire mastering of elementary techniques and of communication skills properly belonging to the fields of economic analysis. Learning skills Students who pass the exam will have acquired analytical methodologies which ail allow them to tackle themes proper of other courses and to discuss current economic facts.
1017529 \| SOCIOLOGY	2nd	9	SPS/07	ITA
Educational objectives Learning goals The Course aims to introduce students to the analysis of the main social phenomena characterizing the contemporary society, highlighting the change processes as well as the aspects of innovation they are concerned with. A special focus will be devoted to the issues of globalization and inequality; migration and integration processes; education an employment; technological innovation and communication, according to a gender and generational perspective. Finally, both the analysis and the interpretation of these phenomena will be accompanied by some key methodological issues rooted in different theoretical approaches and paradigms. Knowledge and understanding At the end of the Course, students will know the main theories and methodological approach to analyse social phenomena. They will learn the main schools of the classical (the positivism of A. Comte and E. Durkheim, the historical materialism of K. Marx, the comprehensive sociology of M. Weber) as well as the contemporary (the culturalism, the School of Chicago, the functionalism of T. Parsons, the structuralism, the sociology of A. Touraine, the School of Francoforte, the methodological individualism, the habitus of P. Bourdieu) sociological thought. Hence, they will learn the different interpretive perspectives of society, of the socialization processes, of the social change, of employment and education, of family structures, and group dynamics (social, political). This knowledge will enable students to both understand some complex social phenomena and formulate appropriate research questions. Applying knowledge and understanding The knowledge acquired enables students to apply theoretical schemes to complex social phenomena, traducing them in concrete research questions, defining objectives and working hypothesis. Moreover, the sociological fundamentals will provide students with the knowledge needed for an in depth interpretation of statistical data related to complex social phenomena. Making judgements Students are constantly involved in active class-work sessions. Indeed, the teaching method aims at encouraging all students, individually or in group, to analyse and critically comment/interpret socio-demographic data of official statistics, in order to develop capacity of synthesis and evaluation with respect to the issues proposed by the lecturer. Communication skills The working group and the presentation/discussion of the results of the class activities (comment and interpretation of statistical data and reports) contribute to both the development of communication skills and the acquisition of the specific scientific technical language of the discipline. Learning skills The sociological fundamentals acquired during the course will enable students to easily identify further references for an in depth study of those topics of personal interest.
AAF1101 \| English language	2nd	3	ENG
Educational objectives ObjectivesThis course aims to give students a solid grounding in statistical terminology and to acquaint them with the typical linguistic features and characteristics of standard statistical presentations and publications.Skills studiedProceeding from the elementary skills of interpreting and describing tables and graphs, the course will focus on expository texts ,so as to enable the students gain facility in describing the statistical methods underlying reported data. It is hoped that by the end of the course, the students, with reference to the publications of the Istitutonazionale di statistica , will be able to make competent statistical presentations in English on the economic and social realities of Italy and to respond to questions and requests for clarification thereon.
Optional group F for 9 CFU/ ECTS

2nd year

Lesson	Semester	CFU	SSD	Language
10612163 \| MATHEMATICAL ANALYSIS II COURSE	1st	6	MAT/05	ITA
Educational objectives Knowledge and understanding. Good theoretical and practical knowledge of differential calculus and integration for functions of several real variables. Ability to understand these issues also in the context of other courses. Applying knowledge and understanding. Ability to use the acquired skills for solving simple problems and for their use required in other courses. Making judgements. Good ability to recognize, frame and set out the resolution of simple problems, selecting appropriately among the methods learned. Communication skills. Good presentation skills of basic concepts and techniques of Mathematical analysis. Learning skills. Good learning ability of mathematical issues in other courses, by virtue of the comprehension of the logical-deductive character of the discipline.
1022318 \| PROBABILITY	1st	9	MAT/06	ITA
Educational objectives Learning goals The primary educational objective of the course is students' learning of the main theoretical aspects related to probability. Students must also be able to solve the analytical problems necessary to apply the aforementioned theoretical concepts. Knowledge and understanding. At the end of the course the students know and understand the main aspects related to the theory of probability and the main methods useful to solve the problems linked to the uncertainty. Applying knowledge and understanding. At the end of the course students are able to formalize problems related to uncertainty in terms of probabilistic problems and to apply the specific methods of the probability to solve them. They are also able to model real phenomena through remarkable probabilistic structures. Making judgements. Students develop critical skills through the application of theory to a wide range of probabilistic models. They also develop the critical sense through the comparison between alternative solutions to the same problem obtained using different methodological aspects. Communication skills. Students, through the study and the practical exercises, acquire the technical-scientific language of the probability, which must be properly used both in the intermediate and final written tests and in the oral tests. Learning skills. Students who pass the exam have learned the basic concepts of probability that allow them to deal with subsequent statistical area teaching (in particular the teaching of Statistical Inference).
1017493 \| DEMOGRAPHY	1st	9	SECS-S/04	ITA
Educational objectives Learning goals The primary educational goal of the course is students' learning of the main concepts and basic methods of Demography. Knowledge and understanding. After attending the course, the students know and understand the statistical-demographic sources and the elementary measures to describe the main demographic phenomena. Applying knowledge and understanding. At the end of the course, the students are able to apply the learned methods to the real data, and to understand the results of these applications. Making judgements. Students develop critical skills through the application of different indicators and measures to a wide range of case studies, and learn to critically interpret the results. Communication skills. The students, through the study and the carrying out of practical exercises, acquire the technical-scientific language of the discipline, which must be opportunely used in the final oral examination. Communication skills are also developed through group activities. Learning skills. Students who pass the exam have learned the skills necessary to address the study of more complex methods and models in subsequent teachings of demographic area.
1026126 \| STATISTICAL INFERENCE AND LABORATORY	2nd	12	SECS-S/01	ITA
Educational objectives Learning goals. The primary educational objective of the course is students' learning of the main problems and methods of statistical Inference and its different alternative theoretical approaches. Students must also be able to solve the analytical problems necessary to apply the above methods and be able to interpret the results that derive from their application to real data. Knowledge and understanding. After attending the course the students know and understand the main inferential problems (point and interval parametric estimation and hypothesis testing of the most important univariate statistical models) and the main methods to be used to solve these problems (for example: maximum likelihood estimation, confidence intervals, parametric tests). Applying knowledge and understanding. At the end of the course the students are able to formalize real problems in terms of inferential problems and to apply the specific methods of the discipline to solve them. They are also able to process the most important statistical models (with one or two unknown parameters) and to apply the methods to models not covered in the lessons. Finally, they are able to apply the methods to the data and to interpret the results. Making judgements. Students develop critical skills through the application of inferential methodologies to a wide range of statistical models. They also develop the critical sense through the comparison between alternative solutions to the same problem obtained using different inferential logics. They learn to critically interpret the results obtained by applying the procedures to real data sets. Communication skills. Students acquire by means of theoretical study and by solving practical exercises, the technical-scientific language of the discipline, which must be properly used both in the intermediate and final written tests and in the oral axam. Communication skills are also developed through group activities stimulated during labs and participation to a public discussion forum Learning skills. Students who pass the exam have learned a method of analysis that allows them to tackle, in future more advanced courses, the study of the formal properties of inferential procedures in more complex modeling contexts.
THREE-DIMENSIONAL MODELING	2nd	3	SECS-S/01	ITA
Educational objectives Learning goals. The primary educational objective of the course is students' learning of the main problems and methods of statistical Inference and its different alternative theoretical approaches. Students must also be able to solve the analytical problems necessary to apply the above methods and be able to interpret the results that derive from their application to real data. Knowledge and understanding. After attending the course the students know and understand the main inferential problems (point and interval parametric estimation and hypothesis testing of the most important univariate statistical models) and the main methods to be used to solve these problems (for example: maximum likelihood estimation, confidence intervals, parametric tests). Applying knowledge and understanding. At the end of the course the students are able to formalize real problems in terms of inferential problems and to apply the specific methods of the discipline to solve them. They are also able to process the most important statistical models (with one or two unknown parameters) and to apply the methods to models not covered in the lessons. Finally, they are able to apply the methods to the data and to interpret the results. Making judgements. Students develop critical skills through the application of inferential methodologies to a wide range of statistical models. They also develop the critical sense through the comparison between alternative solutions to the same problem obtained using different inferential logics. They learn to critically interpret the results obtained by applying the procedures to real data sets. Communication skills. Students acquire by means of theoretical study and by solving practical exercises, the technical-scientific language of the discipline, which must be properly used both in the intermediate and final written tests and in the oral axam. Communication skills are also developed through group activities stimulated during labs and participation to a public discussion forum Learning skills. Students who pass the exam have learned a method of analysis that allows them to tackle, in future more advanced courses, the study of the formal properties of inferential procedures in more complex modeling contexts.
THREE-DIMENSIONAL MODELING	2nd	9	SECS-S/01	ITA
Educational objectives Learning goals. The primary educational objective of the course is students' learning of the main problems and methods of statistical Inference and its different alternative theoretical approaches. Students must also be able to solve the analytical problems necessary to apply the above methods and be able to interpret the results that derive from their application to real data. Knowledge and understanding. After attending the course the students know and understand the main inferential problems (point and interval parametric estimation and hypothesis testing of the most important univariate statistical models) and the main methods to be used to solve these problems (for example: maximum likelihood estimation, confidence intervals, parametric tests). Applying knowledge and understanding. At the end of the course the students are able to formalize real problems in terms of inferential problems and to apply the specific methods of the discipline to solve them. They are also able to process the most important statistical models (with one or two unknown parameters) and to apply the methods to models not covered in the lessons. Finally, they are able to apply the methods to the data and to interpret the results. Making judgements. Students develop critical skills through the application of inferential methodologies to a wide range of statistical models. They also develop the critical sense through the comparison between alternative solutions to the same problem obtained using different inferential logics. They learn to critically interpret the results obtained by applying the procedures to real data sets. Communication skills. Students acquire by means of theoretical study and by solving practical exercises, the technical-scientific language of the discipline, which must be properly used both in the intermediate and final written tests and in the oral axam. Communication skills are also developed through group activities stimulated during labs and participation to a public discussion forum Learning skills. Students who pass the exam have learned a method of analysis that allows them to tackle, in future more advanced courses, the study of the formal properties of inferential procedures in more complex modeling contexts.
1023023 \| TERRITORIAL DEMOGRAPHY	2nd	6	SECS-S/04	ITA
Educational objectives Goals Management of information about mobility and migration. Construction of interpretation/analysis models based on the use of origin/destination matrices. Ability to understand the problems about the construction of functional areas. Skills to acquire Ability to use population sources, especially data about population equilibrium and reconstruction. Management of migration information. Management of data coming from origin/destination matrices. Knowledge of recent immigration literature and the presence of foreigners.
1023028 \| Political Economics II	2nd	6	SECS-P/01	ITA
Educational objectives Learning goals Working knowledge of the main models of economic dynamics Knowledge and understanding Upon succesfull completion of the course, students will be able to analyse actual economic problems in terms of competing theories and models. Applying knowledge and understanding Upon succesfull completion of the course, students will be able to understand the explicit and implicit hypotheses informing the main economic policy proposals in the current debate. Making judgements The course is explicitly based on the principle of methodological and theoretical pluralism. Students will be introduced to at least two competing models for each economic problem considered, and will understand the criteria with which to personally choose their favourite interpretation Communication skills Through study and hands-on sessions, students will become proficient in the jargon and technical language of the discipline, which they must use in both written and oral examinations. Learning skills Students that succesfully complete the course will have learnt a method of analysis that will allow them to tackle and understand the main economic issues of today, both in subsequent economic courses and in the fruition and participation to the public debate
Optional group F for 9 CFU/ ECTS
Optional group C for 27 CFU/ ECTS

3rd year

Lesson	Semester	CFU	SSD	Language
1022894 \| MULTI-VARIED STATISTICS	1st	9	SECS-S/01	ITA
Educational objectives Learning goals. The primary aim of the course is the students' knowledge of the most relevant multivariate statistical methods and their application to real data. Knowledge and understanding. Knowledge of the most applied multivariate techniques in the domains of dependence, classification and latent structures from the exploratory and inferential (multivariate Gaussian case) points of view. Applying knowledge and understanding. Ability to formalize real problems in statistical terms and to solve them by applying the corresponding multivariate methods. Making judgements. Ability to apply multivariate statistical methods and to evaluate the reliability of the results obtained by analyzing real data. Communication skills. By studying and by examples, learning and acquiring technical and scientific language in the statistical domain to be used properly in the final evaluation. Learning skills Students passing the exams acquire the knowledge for facing more complex issues, in more advanced statistical courses, by means of multivariate statistical methods.
1023208 \| METHODOLOGY AND TECHNIQUE OF SOCIAL RESEARCH	1st	6	SPS/07	ITA
Educational objectives Learning goals Capabilities of designing and running a social research. Knowledge and understanding Capability of analyzing social phenomena through middle range theories. Applying knowledge and understanding Capability of choosing techniques for detection, processing, and analysis more suitable to studied phenomena, at the macro, meso, and micro level. Making judgements Capability of research planning, organizing, and self-assessing. Communication skills Capability of team working and appropriately interacting in a multidisciplinary statistical-sociological team. Learning skills Capability of autonomous search of statistical, web, and bibliographical sources, necessary for doing research.
Elective course	1st	12	ITA
Educational objectives This course can be chosen by the student within the Sapienza courses as long as consistent with the curriculum.
1017262 \| SAMPLING TECHNIQUES	2nd	6	SECS-S/01	ITA
Educational objectives Learning goals The primary goal of the present course is to allow students to learn the main elementary techniques and methodologies for sampling finite populations and estimate population parameters. Students should be able to plan a sample survey and analyze collected data in order to provide point and interval estimates of the population parameters. Knowledge and understanding Students are expected to have a good knowledge of the main elementary sampling designs (simple random sampling, stratified sampling, single-stage cluster sampling, two-stage sampling, systematic sampling) as well as a basic knowledge of variable-probability sampling designs. Applying knowledge and understanding Students should be able to formalize real problems involving survey sampling and should use acquired knowledge to solve real problems. Furthermore, they should be able to estimate parameters of interest even in the presence of auxiliary variables. Making judgements Students should develop their skills by planning sample surveys. Communication skills Students should learn the appropriate language of survey sampling. Learning skills Students should be able to attack the problem of planning a sample survey by using elementary sampling designs. This is the typical case of surveys on a small/medium scale.
AAF1004 \| Final exam	2nd	6	ITA
Educational objectives The final exams consists of writing, presenting and discussing a thesis, developed autonomously by the students, which illustrates in a coherent and detailed manner the problem tackled during the practical training and all the activities carried out to develop its solution.
Optional group C for 27 CFU/ ECTS
Optional group F for 9 CFU/ ECTS

Optional groups

The student must acquire 9 CFU from the following exams

Lesson	Year	Semester	CFU	SSD	Language
AAF2347 \| Preparatory Mathematics	1st	1st	3	ITA
Educational objectives Learning goals Knowledge and comprehension of the basic concepts and techniques of linear algebra and of analytic geometry of the plane and the space and ability to apply them to the study and resolution of simple problems also in the context of other courses. Knowledge and understanding. Good theoretical and practical knowledge of matrices, linear systems and other fundamental notions of linear algebra and ability to understand these issues also in the context of other courses. Applying knowledge and understanding. Ability to use the acquired skills for solving simple problems on matrices, linear systems and other fundamental notions of linear algebra, also for their use required in other courses. Making judgements. Good ability to recognize, frame and set out the resolution of simple problems on matrices, linear systems and other fundamental notions of linear algebra, possibly selecting appropriately among the methods learned. Communication skills. Good presentation skills of basic concepts and techniques of linear algebra as well as solution methods to simple problems. Learning skills. Good learning ability of mathematical issues in other courses, by virtue of the comprehension of the logical-deductive character of the discipline.
AAF2455 \| Excel Lab. Basic and Advanced Course	1st	2nd	3	ITA
Educational objectives Learning goals The learning goal of the Laboratory is the knowledge of the main functions and tools of Excel, with particular attention to functionalities useful in the field of empirical social research. The aim is to provide students with knowledge that enables them to work independently with Excel, becoming familiar with the software interface and syntax, and acquiring the skills necessary to perform research operations such as: - Data storage and construction of a new matrix; - Management of databases and differently constructed data matrices; - Data cleaning and pre-processing of different type of information; - Recoding of variables; - Sampling procedures involving simple random extraction of cases; - Calculation of descriptive statistics of cardinal variables; - Mono and bivariate data analysis using specific functions and tools; - Production of graphs and tables. Students will acquire theoretical and methodological knowledge by implement what was explained by the teacher, thanks to the alternation of lectures, practical activities (individual work and teamwork) and moments of discussion in the classroom. Knowledge and understanding Students will face in practice the main phases of data cleaning, pre-processing, and statistical- descriptive analysis. At the end of the laboratory, students will have learned the functions and tools of Excel that allow them to manage databases and data matrices, perform recoding operations of variables, pre-process unstructured textual data, perform mono and bivariate data analysis, as well as develop graphical representations. Applying knowledge and understanding Through practical experience, students will learn: how to store and organize information in a matrix built from scratch; how to handle and manage databases obtained through platforms for building and compiling online questionnaires or exported from other statistical analysis software; how to choose the most suitable tools and procedures to carry out specific data cleaning, processing, and analysis operations; how to present the results of data analysis through the production of graphs and tables. Making judgements Revisiting the various methodological phases of data processing and analysis, students acquire judgment, decision-making and problem-solving skills thanks to an experience of cooperative learning, which encourages constant discussion among peers and with the teacher. Communication skills Participation in group work and discussion in the classroom of the practical results obtained at the end of each practical session enhances students' communication skills. In particular, these activities allow improving communication strategies in peer-to-peer discussions and offer the opportunity to practice public speaking. Learning skills The applied research activity allows students to broaden the theoretical knowledge already acquired and to strengthen the theoretical and practical learning capacity of advanced approaches, methods and techniques for analyzing social phenomena.
AAF1456 \| Laboratory of probability	2nd	1st	3	ITA
Educational objectives Learning goals The primary educational objective of the course is students' learning of the main applied aspects related to probability. Knowledge and understanding At the end of the course the students know and understand the main methods useful to solve the problems linked to the uncertainty. Applying knowledge and understanding At the end of the course students are able to formalize problems related to uncertainty in terms of probabilistic problems and to apply the specific methods of the probability to solve them. They are also able to model real phenomena through remarkable probabilistic structures. Making judgements Students develop critical skills through the application of theory to a wide range of probabilistic models. They also develop the critical sense through the comparison between alternative solutions to the same problem obtained using different methodological aspects. Communication skills Students, through the study and the practical exercises, acquire the technical-scientific language of the probability, which must be properly used in the oral test. Learning skills Students who pass the exam have learned the basic concepts of probability that allow them to deal with subsequent statistical area teaching (in particular the teaching of Statistical Inference).
AAF2040 \| Soft skills	2nd	2nd	3	ITA
Educational objectives The goal is to provide students with the so-called soft skills, useful for future academic and professional activities. They include: public speaking, ability in producing scintific written reports, use of scientific text editors (e.g. Latex), team working, etc.
AAF2577 \| Text mining Laboratory	3rd	1st	3	ITA
AAF1377 \| Social Research Lab	3rd	2nd	3	ITA
Educational objectives Learning goals. The main learning goal of the Laboratory concerns the definition and the development of the whole process of a social research from its design and planning up to the field-work, the data analysis and their representation in a statistical report. The lessons and the practical activities of the teaching programme are well balanced in order to enable students to apply the theoretical concepts learned during the lessons. Knowledge and understanding. At the end of the Laboratory students know all the phases of the process design and planning as well as the correspondent specific activities. Students learn the main techniques a) to conceptualize research problems; b) to build up data collection tools (paper and electronic questionnaires); c) to gather data. Moreover, students learn how to interpret and comment survey data, reporting the contents in an effective way. Applying knowledge and understanding. The practical experience of applied research enable students to formulate research questions, objectives and hypothesis; to identify the most appropriate data collection tools; to build up a data collection tool (paper and electronic questionnaire); to monitor the data collection activity; to analyse and interpret data. Students experience the redaction of a report summarizing the main results of the survey they have conducted. Making judgements. The students working in group are constantly encouraged to discuss and share ideas, in order to acquire capacity of decision and problem solving with respect to the choices related to the realization of a social research. Moreover, the students improve their ability to interpret data. Communication skills. The working group and the presentation of the results of the tasks assigned by the lecturer contribute to the development of communication skills. The presentation and discussion of the final report contribute to the acquisition of the specific scientific technical language of the discipline. Learning skills. The practical experience of research of the Laboratory enable students to strengthen their theoretical knowledge and to improve the capacity to learn more advanced methods and techniques of survey management.
AAF2518 \| Laboratory of statistical learning	3rd	2nd	3	ITA

The student must acquire 27 CFU from the following exams

Lesson	Year	Semester	CFU	SSD	Language
1010576 \| SOCIAL STATISTICS	2nd	2nd	9	SECS-S/05	ITA
Educational objectives Learning goals The primary educational objective of teaching is to show students how to apply the notions of descriptive and inferential Statistics to the specific issues of society. Furthermore, students must be able to manage a data base, deriving from a questionnaire survey, or from a secondary analysis on indicators, produced by an official statistical source, at national and international level. Knowledge and understanding After attending the course, the students will be able to understand the meaning and the role of the main statistical tests and the main strategies for the synthesis of univariate, bivariate and multivariate data. Applying knowledge and understanding At the end of the course the students will be able to apply the above tests and synthesis strategies on real data bases, taken as case studies. Making judgements Students will develop critical skills by comparing the results obtained with the application of different methods on the same real data bases. They will learn to contextualise the results obtained in the various social, economic and cultural spheres. Communication skills The students, through the study and the carrying out of practical exercises, acquire the technical-scientific language of the discipline, which will be opportunely used both in the exercises during the work, also in groups, and in the presentation of results of autonomous elaborations, both in the final oral exam. Learning skills Students who pass the exam learned a method of analysis that will allow them to understand the opportunities and limitations of the statistical approach to social, economic and cultural problems.
1036199 \| THEORIES AND TECHNIQUES OF PSYCHOLOGICAL TESTS	3rd	1st	9	M-PSI/03	ITA
Educational objectives GENERAL AIMS The course aims to provide the student with a methodological framework for the quantitative assessment of cognitive, general and specific skills, and of the personality traits, both normal and pathological, through psychological tests, as well as deepening the statistical methods underlying the construction of these tests and the verification of their psychometric properties (reliability and validity). The lectures therefore have the purpose of integrating the conceptual aspects of psychometry (reliability, validity) with the psychology theories of intelligence and personality. The goal is to prepare the student to apply the methods of data analysis necessary to evaluate the psychometric properties of a test, and to learn how to choose a test, administer it correctly and interpret the scores obtained. SPECIFIC AIMS Knowledge and understanding The student must demonstrate that he/she has acquired the basic knowledge and skills related to the construction, use and interpretation of tests in the profession and in psychological research. Applying knowledge and understanding The student must be able to interpret the data analysis necessary to demonstrate the reliability and validity of the tests. Moreover, under the supervision of a professional psychologist, he / she should be able to: consciously use a wide range of psycho-metric tools for psychological assessment; to know how to choose to administer, to interpret the main psychological tests for the evaluation of personality and intelligence. Making judgements The student must be able to assess critically and autonomously how to use different psychological tests, how to deal with ethical and deontological issues related to psychology evaluation, how to interpret the test results in a mindful way. Communication skills The student will be able to elaborate written materials and oral presentations able to communicate the knowledge (for example nature and use of psychological tests) to specialists and non-specialist stakeholders. Learning skills Through the lectures the student will acquire learning skills that can be spent in the specific context of psychometrics applied in different disciplinary fields, and in the more general autonomy in the reading of advanced scientific texts, which will be addressed during the studies, and in particular in the preparation of the "laurea" degree dissertation, as well as necessary to address the master's degree courses.
10621372 \| Methodologies and techniques of social work	3rd	1st	9	SPS/07	ITA
98431 \| INTERNATIONAL ECONOMY	3rd	1st	9	SECS-P/01	ITA
Educational objectives The course develops a systematic understanding of the key areas of international economics: trade, migration and international monetary economics, and their impact on each other. Theory will be applied to events, problems and trends in the international economy. Since international economics is dynamic in nature and influenced by real-world developments in the economic, political and financial spheres, the course coverage will be updated periodically to include recent developments/conditions in the real-world environment. (a) knowledge and understanding; After taking the course, students will be able to understand and define the main concepts, models and patterns of analysis of the three key areas of international economics: trade, migration and international monetary economics. (b) Applying knowledge and understanding; By the end of the course, students will be able to formalize real economic problems and apply discipline-specific methods to analyze them in detail. Students will acquire a theoretical background and, through the analysis of practical cases, the ability to critically study economic policies and models in the context of international trade. (c) Making judgments Students will increase not only their theoretical skills but also their critical curiosity in reading economic phenomena and economic models from an open economics perspective. (d) Communication skills Students/youth, through class discussions and exercises, will acquire tools for critical analysis and communication skills. They will acquire the technical and scientific language of the discipline; they will also learn how to structure and present a research report. (e) Learning skills Students who pass the exam will have learned notions, definitions, patterns of analysis and methods of analysis that will enable them to take other courses in economics and social sciences.
10589727 \| ECONOMICAL AND POLITICAL GEOGRAPHY	3rd	2nd	9	M-GGR/02	ITA
Educational objectives The aim is to provide students with the interpretive spatial means functional to understanding the actions of the entities operating in the political and economic fields. They are necessary to grasp the complexity and the interrelations between the territory’s different geopolitical and geo-economic phenomena. The theoretical framework will be applied to actual instances of geopolitical instability on different levels of analysis. Knowledge of basic notions in geography, as well as in the most recent developments in geopolitically relevant international matters, is required. In this regard, it is highly recommended that students prepare for the exam by making use not only of up to date atlases but also of specialized magazines. Visiting authoritative websites which focus on geopolitical themes is also advised.
1024055 \| Statistics for Experimental Research	3rd	2nd	9	SECS-S/02	ITA
Educational objectives Learning goals The main educational objective of the course is the learning of the linear model analysis in its theoretical, methodological and applicative aspects. Students must master language and the principles of statistical analysis in the experimental field. Knowledge and understanding. After having attended the course the students know and know how to apply the methods of analysis of the Linear Model, in the various experimental, observational and quasi-experimental situations. Applying knowledge and understanding. At the end of the course the students are able to identify which types of situations can be analyzed with the linear model tools, and to formalize them in terms of parametric statistical models. They are also able to formulate substantive questions in parametric terms, in different situations, and answer to these questions with the tools of statistical analysis. Making judgements. Students develop critical skills through the application of inferential methodologies to a wide range of situations that can be represented in the linear model family. They also develop the critical sense through the selection, estimation and validation procedure of the statistical model in different situations related to real data. Communication skills. Particular attention is paid to the technical-scientific language of the discipline, which must be used correctly in the final test. Learning skills. Students who pass the exam have acquired the fundamentals of the parametric models that allow them to face the study of more complex models.
98457 \| ECONOMIC STATISTICS	3rd	2nd	9	SECS-S/03	ITA
Educational objectives Learning goals. An introduction to the basic skills of empirical economic analysis Knowledge and understanding. After taking the course the students know and understand the main problems in measuring economic variables and the methods to be used to solve them. Applying knowledge and understanding. After taking the course the students know how to solve the main problems in measuring economic variables. Making judgements. Students develop their critical skills through the analysis of real datasets. Communication skills. Students acquire the technical language, which must be used both in the written exam and in the individual project. Learning skills. Students passing the exam have acquired the ability to read and realise basic empirical economic studies.
1018133 \| ECONOMETRICS	3rd	2nd	9	SECS-P/05	ITA
Educational objectives Learning goals. The aim of the lectures is to provide an exhaustive discussion of the main topics concerning the linear model (OLS, MLE, IV, asymptotic theory and inference) for cross-section analysis and a brief introduction to the analysis of discrete data. Students must understand the analytical problems of these methods and be able to apply them to concrete situations. Knowledge and understanding. After attending the course the students know and understand the main problems related to the linear regression model (for example: absence of exogeneity) and the main methods to be used to solve such problems (for example: IV estimator). Applying knowledge and understanding. At the end of the course the students are able to formalize real problems in terms of linear regression models and to apply the methods specific to the discipline to solve them. They are also able to apply the methods to concrete situations and to interpret the results. Making judgements. Students develop a knowledge of the analytical properties of the presented methodologies and the ability to build programs for their implementation. They also learn to critically interpret the results obtained by applying the procedures to concrete situations. Communication skills. Students acquire the technical-scientific language of the discipline, which it must be used appropriately in both the intermediate and final written tests and in the oral tests. Communication skills are also developed through group activities. Learning skills. Students who pass the exam have learned a method of analysis that allows them to tackle the study of analytical properties in more complex modeling contexts in subsequent quantitative area teachings.