- Docente: Luca Trapin
- Credits: 6
- SSD: SECS-S/02
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
-
Corso:
Second cycle degree programme (LM) in
Digital Humanities and Digital Knowledge (cod. 9224)
Also valid for Second cycle degree programme (LM) in Innovation and Organization of Culture and the Arts (cod. 0902)
Learning outcomes
techniques concerning the analysis of data bases. In particular the student is expected to learn: - probability s tools - measures of variance - index numbers
Course contents
1. Data collection, management and visualization
2. Descriptive statistics
3. Foundations of probability
4. Statistical inference
4.1 Sampling
4.2 Estimation
4.3 Hypothesis testing
5. Simple regression
Readings/Bibliography
Suggested book
Luca Trapin, Lecture Notes for Basics Analytics.
Gary Smith, Essential Statistics, Regression, and Econometrics, Academic Press (Elsevier).
David Spiegelhalter, The Art of Statistics: Learning from Data, Pelican Book.
Teaching methods
Class lessons
Assessment methods
Written examination: theoretical questions and exercises
Grading system:
- <18: fail
- 18-23:sufficient
- 24-27: good
- 28-30: very good
- 30 e lode: excellent
Teaching tools
Class notes on IOL
Office hours
See the website of Luca Trapin
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.