- Docente: Maria Letizia Guerra
- Credits: 3
- SSD: SECS-S/06
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Statistical Sciences (cod. 9222)
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from Apr 16, 2025 to May 21, 2025
Learning outcomes
By the end of the course the student learns the advanced methods and the operational tools for the analysis of (fuzzy) set-valued data. The student is able to face the theoretical problems of analysing statistical properties within these kind of data and their application to social sciences
Course contents
The Concept of Fuzziness
Interval data: structures and statistics
Generalizations of interval data
Fuzzy Sets valued data
Fuzzy sets algebra
Mathematical modeling
Fuzzy clustering
F-Transform
Readings/Bibliography
Vilém Novák, Irina Perfilieva, Insight into Fuzzy Modeling, 2016 John Wiley & Sons.
Renato Coppi, Maria A. Gil, Henk A.L. Kiersc, The fuzzy approach to statistical analysis, Computational Statistics & Data Analysis 51 (2006) 1–14
Teaching methods
After 10 hours of frontal lectures, the method changes in flipped classroom and students are invited to collaborate in team and present the analysis of a statistical application to real world data or phenomenon.
Assessment methods
The exam is based on the discussion of a scientific paper agreed with the teacher where an application is explained.
Teaching tools
Several packages for fuzzy calculus are available in R and MatLab libraries.
Office hours
See the website of Maria Letizia Guerra
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.