The epistemology of big data
A.A. 2024/2025
Obiettivi formativi
The course aims at developing the logico-mathematical background to assess critically the logic and episte-mology of inductive reasoning, or "reasoning with data". In addition to making students familiar with the rel-evant elementary logical, probabilistic and statistical notions, it focusses on how the formalisation of induc-tive inference sheds crucial methodological light on the "datacentric" revolution, which is currently dotting the development of the natural and social sciences.
Risultati apprendimento attesi
Students are expected to acquire a full understanding of the formal notions presented and master basic knowledge of the following topics:
- know the central concepts and reasoning tools of discrete mathematics
- know the central concepts in elementary probability theory
- know how to apply elementary logic to formalize probabilistic concepts
- understand the epistemological questions related to inductive reasoning
- understand the relevance of a proper the epistemology of inductive inference in the wider methodological discussion on "big data"
- know the central concepts and reasoning tools of discrete mathematics
- know the central concepts in elementary probability theory
- know how to apply elementary logic to formalize probabilistic concepts
- understand the epistemological questions related to inductive reasoning
- understand the relevance of a proper the epistemology of inductive inference in the wider methodological discussion on "big data"
Periodo: Secondo semestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento può essere seguito come corso singolo.
Programma e organizzazione didattica
Edizione unica
Responsabile
Periodo
Secondo semestre
Programma
1. Reasoning with data
- Data and its meaning
- Elementary descriptive statistics
- Elementary probability
2. The epistemology of reasoning with data: induction
- Induction and knowledge
- More data vs better data
- Data and its meaning
- Elementary descriptive statistics
- Elementary probability
2. The epistemology of reasoning with data: induction
- Induction and knowledge
- More data vs better data
Prerequisiti
None
Metodi didattici
Frontal and flipped lectures and assignments. The approach will be problem-oriented and students will be trained to learn by solving basic problems and exercises
Materiale di riferimento
Modalità di verifica dell’apprendimento e criteri di valutazione
The exam is written, it is taken online, and it is marked as follows:
- End-of-course project: 50% of the final mark
- Online questions-based exam / flipped classroom activities: 50% of the final mark
- End-of-course project: 50% of the final mark
- Online questions-based exam / flipped classroom activities: 50% of the final mark
Siti didattici
Docente/i
Ricevimento:
Venerdì 8:30-11:30
Secondo Piano, Cortile Ghiacciaia. Affinché possa garantirvi il colloquio, vi prego di prenotarvi per email