Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Study Plan

A.A. 2024/2025 A.A. 2023/2024 A.A. 2022/2023 A.A. 2021/2022 A.A. 2020/2021 A.A. 2019/2020 A.A. 2018/2019 A.A. 2017/2018 A.A. 2016/2017 A.A. 2015/2016 A.A. 2014/2015 A.A. 2013/2014 A.A. 2012/2013 A.A. 2011/2012 A.A. 2010/2011 A.A. 2009/2010

This information is intended exclusively for students already enrolled in this course.
If you are a new student interested in enrolling, you can find information about the course of study on the course page:

Laurea in Informatica - Enrollment from 2025/2026

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

1° Year

ModulesCreditsTAFSSD
6
A
MAT/02
6
A
MAT/05
12
A
ING-INF/05
6
A
FIS/01
6
A
INF/01
6
C
MAT/06
12
A
INF/01
English language competence-complete b1 level
6
E
-

2° Year  activated in the A.Y. 2017/2018

ModulesCreditsTAFSSD
12
B
INF/01
6
C
MAT/05
6
C
FIS/01
12
B
INF/01
6
B
ING-INF/05
12
B
ING-INF/05
One course to be chosen among the following
6
B
INF/01
6
B
INF/01

3° Year  activated in the A.Y. 2018/2019

ModulesCreditsTAFSSD
12
B
ING-INF/05
6
B
INF/01
6
B
INF/01
6
B
INF/01
One course to be chosen among the following
6
B
INF/01
6
B
INF/01
6
F
-
12
D
-
Prova finale
6
E
-
ModulesCreditsTAFSSD
6
A
MAT/02
6
A
MAT/05
12
A
ING-INF/05
6
A
FIS/01
6
A
INF/01
6
C
MAT/06
12
A
INF/01
English language competence-complete b1 level
6
E
-
activated in the A.Y. 2017/2018
ModulesCreditsTAFSSD
12
B
INF/01
6
C
MAT/05
6
C
FIS/01
12
B
INF/01
6
B
ING-INF/05
12
B
ING-INF/05
One course to be chosen among the following
6
B
INF/01
6
B
INF/01
activated in the A.Y. 2018/2019
ModulesCreditsTAFSSD
12
B
ING-INF/05
6
B
INF/01
6
B
INF/01
6
B
INF/01
One course to be chosen among the following
6
B
INF/01
6
B
INF/01
6
F
-
12
D
-
Prova finale
6
E
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Probability and Statistics (2016/2017)

Teaching code

4S02843

Credits

6

Coordinator

Bruno Gobbi

Language

Italian

Also offered in courses:

Scientific Disciplinary Sector (SSD)

MAT/06 - PROBABILITY AND STATISTICS

MoodleMoodle Seminars 0

The teaching is organized as follows:

Teoria

Credits

4

Period

II sem.

Academic staff

Bruno Gobbi

Laboratorio [II turno]

Credits

2

Period

II sem.

Academic staff

Bruno Gobbi

Laboratorio [I turno]

Credits

2

Period

II sem.

Academic staff

Bruno Gobbi

Learning outcomes

The goal of the course is to introduce theoretical basis of descriptive statistics and probability, in order to solve the problem of modelling actual phenomena by using stochastic methods, especially applied to Statistics.
By the end of the course, students will have to show their skills with the main statistical methodologies for the analysis and estimation of phenomena, both theoretically and through the use of the R-Studio software.

Program

Descriptive statistics. Means, median, quantiles.
Variance and other statistics to measure the variability of a distribution.
Simmetry: Skewness of Pearson.
Independence test in crossed tables.
Linear Regression.
Introduction to probability theory: historical roots, three kinds of definition. Revision of set theory. Axiomatic definition of probability: outcomes, random experiments, sample space. Conditional probability: total probability theorem, law of compound probabilities.
Combinatorics elements: dispositions, permutations, combinations.
Random variables, discrete density function and cumulative distribution function. Mean, variance and n-th moment of random variables. Models of discrete distributions: Bernoulli distribution, uniform distribution, binomial distribution, geometric distribution, hyper-geometric distribution, Poisson distribution. Examples of continuous distributions: exponential distribution, Gaussian distribution. Characteristic function and (moment) generating function.
Inferential statistics: parameters estimation and statistical hypothesis testing.

Bibliography

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Teoria P. Baldi Calcolo delle Probabilità e Statistica Mc Graw-Hill   8838607370
Teoria D. OLIVIERI Fondamenti di statistica (Edizione 3) Cedam, Padova 2007
Teoria OLIVIERI D. Temi svolti di statistica (2001-2007) CEDAM 2008

Examination Methods

Written exam and test by using the R programming language.

The exam is divided into two parts: a Theory module (22 points) and a Laboratory module (8 points), to be held together.
The test will consist of:
- 3 exercises to be performed with paper, pen and calculator, related to the Theory module;
- 2 exercises about the R programming language, to be performed with paper and pen, related to the Laboratory module.

It is forbidden to use textbooks, manuals or notes during the exam.
Students may use a scientific calculator.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Teaching materials e documents