Provide statistical tools relevant to specific applications and the experience of on-field experts.
At the end of the course the student will be able to
Measurement models in psychometrics (3 credits) Provide an introduction to the theory of psychometrics for statisticians and also provides computer tools (R software) to perform simple basic psychometric analyses.
Demography Provide an introduction to demographics to be able to communicate demographic data to the average citizen.
Risk analysis in banking Present the main statistical models used by the risk manager to measure the various risks in the banking system.
Statistical analysis of complex networks Provide an introduction to methods, models, and computer tools (R software) for the statistical analysis of relational data.
Multiple hypothesis tests Provide the essential tools to understand the problem of the multiplicity of statistical tests and its consequences, including different error measures in the case of Multiple Hypothesis Testing, know different statistical techniques commonly used in the case of Multiple Hypothesis Testing.
Seminars on other applied aspects of mathematical statistics, could be presented by experts such as data scientists working in companies or public bodies.
At the end of the course, the student will be able to
Measurement models in psychometrics (3 credits) Introduction to the theories and methods of psychometrics for students of statistics and mathematics as well as to the IT tools (R software) for carrying out basic psychometric analyzes.
Demography of Italy and the world: issues, data and measures (6 hours – guest lecturer: Gianpiero Dalla Zuanna – College of Padua) Introduction to demography in order to be able to communicate demographic data to the average citizen.
Risk analysis in banking (6 hours – guest lecturer: Luca Piccardo – BPER Genova) Presentation of the main statistical models used by risk managers to measure the different risks in the banking system.
Statistical analysis of complex networks (6 hours – Guest lecturers: Isabella Gollini and Alberto Caimo – College College Dublin) Introduction to the methods, models and software for performing statistical analysis of relational data.
Multiple hypothesis testing (6 hours – guest lecturer: Federico Rotolo – Sanofi Marsiglia) Providing the basic tools to understand the problem of multiple statistical tests and their consequences, the different error measures in multiple hypothesis testing, the different statistical techniques commonly used in multiple hypothesis testing.
These modules can be complemented by seminars on other applied aspects of mathematical statistics, usually given by data scientists from business, consumer companies and public institutions
Fundamentals of inferential statistics and basic R. Basics of Mathematical Statistics.
Combination of traditional lectures and laboratory sessions.
Having a predominantly seminary character and involving external teachers, these activities are reserved for at students who can regularly attend lessons. Those who are interested but unable to attend regularly must agree with the teachers on the methods of participation before including these activities in the study plan.
Psychometrics
Examples of parsing with R will be shown (packages 'psych', 'lavaan', 'mirt')
Demography Collection, analysis and presentation of data are presented as tools to help society to organize themselves in order to transform opportunities into new realities. The main statistical and mathematic tools are introduced to measure demographic phenomena, to interpret them and to predict them. The interdisciplinary nature of demography is highlighted.
Risk analysis in the banking sector In the current banking context characterized by an increasingly competitive market and complex regulations, the Risk Management activity plays a fundamental and strategic role. Our goal is to show how this feature helps banks manage risk. We will start with a description of the main functions of a bank and move on to the use of statistical models to measure the level of various risks.
Statistical analysis of complex networks In order to provide participants with a general understanding of statistical methods for the analysis of complex networks, two families of statistical models will be introduced: exponential models for random graphs and latent variable models.
Multiple Hypothesis Testing The program is in four parts: 1. Statistical tests. Significance level, probability of false negative, power. 2. Multiplicity of tests and consequences. Cherry picking. 3. Error measurements (FWER, FDR). Correction methods for Multiple Hypothesis Testing. 4. Examples in clinical research and FDA guidelines.
Psychometrics Furr, M. R. (2011). Scale Construction and Psychometrics. London, UK: Sage. Material provided by the lecturer (slides, R codes).
Demography Material provided by the lecturer. Gianpiero Dalla Zuanna e Guglielmo Weber (2012). Cose da non credere. Il senso comune alla prova dei numeri. Laterza. Gianpiero Dalla Zuanna e Stefano Allievi (2015). Tutto quello che non vi hanno mai detto sull'immigrazione, Laterza. Maria Castiglioni e Gianpiero Dalla Zuanna (2018). La famiglia è in crisi. Falso! Laterza.
Risk analysis in the banking sector Material and R codes provided by the lecturer.
Statistical analysis of complex networks Material and R codes provided by the lecturers.
Multiple Hypothesis Testing - Dmitrienko, D’Agostino, 2013, Traditional multiplicity adjustment methods in clinical trials. Stat Med 32 - Goeman J, Solari A, 2014, Multiple Hypothesis Testing in Genomics. Stat Med 33 - FDA, 2017, Multiple Endpoints in Clinical Trials. Draft Guidance for Industry. UCM536750
Ricevimento: Students can request an appointment via e-mail to the lecturer so that the day, time and place can be agreed upon. In presence, office hours are usually held in the lecturer's office at the Department of Education, Corso A. Podestà, 2, Room 4A3 (4th floor), 16128 Genoa Online the office hours are held on the Teams channel "Ricevimento Chiorri," which can be accessed with the code 710t4r2 Teachers' contacts E-mail
Ricevimento: For organizational issues contact by email Eva Riccomagno <eva.riccomagno@unige.it>
September 22, 2025
Psychometrics: Written and oral discussion Demography: Questionnaire with closed and open questions Official Statistics: Questionnaire with closed and open questions and oral discussion Risk analysis in the banking sector: Questionnaire with closed and open questions and group project
The final grade is the weighted average of the grades of the various parts. The weights are the hours (equivalently the number of credits) of frontal teaching.
Psychometrics: The student will be provided with a dataset on which to perform some of the analyzes presented during the course. On the basis of what has been learned and from the study material, in the written essay the student is asked to create, interpret and comment on the results and highlight any critical issues. In the oral discussion, any issues in the written essay will be commented on and the student's preparation on psychometric theory will be investigated. Demography: the student's ability to find precise information and data in a complex popular text, as well as identifying the statistical methodology used for the analyses reported in the text. Risk analysis in the banking sector: the ability to apply the mathematical/statistical techniques learned, interpret the results, recognize their value and reliability. Statistical analysis of complex networks: the ability to complete a project in which to implement and interpret some analyses of models introduced in the course using real data. Multiple Hypothesis Testings: the ability to discuss the definition and meaning of main concepts and to deal with practical cases.
Students who have valid certification of physical or learning disabilities on file with the University and who wish to discuss possible accommodations or other circumstances regarding lectures, coursework and exams, should speak both with the instructor and with Professor Sergio Di Domizio (sergio.didomizio@unige.it), the Department’s disability liaison.
