CODE 108209 ACADEMIC YEAR 2025/2026 CREDITS 8 cfu anno 3 POLITICHE, GOVERNANCE E INFORMAZIONE DELLO SPORT 11633 (L-36) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR SECS-S/05 LANGUAGE Italian TEACHING LOCATION GENOVA SEMESTER 1° Semester OVERVIEW The course guides students toward a quantitative approach to understanding sports, both in relation to individual and team performance, and to sport as a social phenomenon. AIMS AND CONTENT LEARNING OUTCOMES The teaching provides students with the basic elements of sports data analysis by forming the knowledge and skills necessary to reorganize statistical information into simple reports using frequency tables, graphs and the main statistical summary indices. Particular attention will be given to the study of the relationship between variables, especially the concepts of correlation and linear regression. The proposed application contexts will be coherent with the sports field and will facilitate the transfer of the acquired competences to the students' chosen study path. In the last part of the teaching, some in-depth studies on probability calculation and statistical sampling useful to model the variability of sports results of teams or individual athletes will be proposed, also to account for some new professions in the sector, such as the ones of match analyst and technological scout. AIMS AND LEARNING OUTCOMES The teaching follows a didactic path on descriptive and inferential statistics that caters to the educational interests of both those who have already taken basic statistics courses and those attending a statistics course for the first time. Knowledge and Understanding: Adequate knowledge is acquired on quantitative analysis methods and the interpretation of the obtained results. Ability to Apply Knowledge and Understanding: The ability to independently apply the learned analysis methods to new data and to produce simple quantitative reports that can be useful in the decision-making process of public administration. Judgment Autonomy: Students are able to assess the quality of the available statistical data and choose the most appropriate analysis method based on their informational needs. Communication Skills: Students acquire the fundamental statistical vocabulary to communicate clearly and unambiguously with both specialist and non-specialist interlocutors. Learning Skills: Students will be able to further explore statistical methods for social sciences by applying them with the software used in class. PREREQUISITES None. TEACHING METHODS Lectures with in-class exercises. SYLLABUS/CONTENT From data to information: statistics as a method Sources of statistical information on sports Describing data using tables, charts, and summary measures Measures of association and correlation Linear regression Basics of probability and statistical inference Principles of statistical surveys in sports: questionnaire design, modes of administration, sampling methods, market research Statistics, sport, and society RECOMMENDED READING/BIBLIOGRAPHY di Bella E. (2025). Metodi statistici per gli sport. Giappichelli. Forthcoming. TEACHERS AND EXAM BOARD ENRICO DI BELLA Ricevimento: Office hours are usually Wednesdays from 4.30 p.m. to 5.30 p.m. on Teams. If a meeting in presence is requested, the teacher's studio is located on the 5th floor of the West Tower of the Albergo dei Poveri's teaching centre. The students of the Department of Economics can arrange a reception by appointment. LESSONS LESSONS START 1st semester Class schedule The timetable for this course is available here: Portale EasyAcademy EXAMS EXAM DESCRIPTION The exam will be conducted exclusively in written form and in an open-book format. The test consists of three theoretical questions and three practical exercises. ASSESSMENT METHODS The theoretical questions in the written exam are designed to assess students’ reasoning skills when faced with new problems, for which they are required to identify and propose an appropriate method of data analysis. The written exam also evaluates the ability to solve simple practical problems based on the availability of real data, selecting the most suitable statistical techniques according to the nature of the data and the specific characteristics of the problem.
