- Docente: Simone Tiberi
- Credits: 9
- SSD: SECS-S/01
- Language: English
- Teaching Mode: In-person learning (entirely or partially)
- Campus: Bologna
- Corso: First cycle degree programme (L) in Business and Economics (cod. 8965)
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from Feb 11, 2026 to May 15, 2026
Learning outcomes
By the end of this course students are able to: - analyze a dataset using numerical indexes and graphical representations; - apply basic tools of probability theory; - produce estimates of population parameters from sample data; - evaluate statistical hypotheses; - apply least square regression analysis.
Course contents
- Introduction to data: Data basics; Sampling principles; Experiments and observational studies
- Summarizing data: Examining numerical data; Considering categorical data
- Probability: Defining probability; Conditional probability; Bayes theorem
- Random variables: Discrete and continuous; Expectation;
- Distributions of random variables: Normal; Geometric; Bernoulli; Binomial
- Foundations for inference: Point estimates; Confidence intervals; Hypothesis testing
- Linear Regression
Readings/Bibliography
David M Diez, Christopher D Barr, Mine C ̧etinkaya-Rundel (2015). OpenIntro Statistics (Fourth Edition).
You can download a free pdf version here: https://openintro.org/book/os/
Teaching methods
Lectures.
Assessment methods
Written exam, with multiple open questions about all topics covered.
Teaching tools
Virtuale (virtuale.unibo.it) contains all the material used during the classes.
Links to further information
https://www.unibo.it/sitoweb/monica.chiogna2/
Office hours
See the website of Simone Tiberi
SDGs
This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.