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.

A.A. 2017/2018

Academic calendar

The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technical-administrative staff of the University. Public holidays and University closures are also indicated. The academic year normally begins on 1 October each year and ends on 30 September of the following year.

Academic calendar

Course calendar

The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..

Definition of lesson periods
Period From To
I sem. Oct 2, 2017 Jan 31, 2018
II sem. Mar 1, 2018 Jun 15, 2018
Exam sessions
Session From To
Sessione invernale d'esame Feb 1, 2018 Feb 28, 2018
Sessione estiva d'esame Jun 18, 2018 Jul 31, 2018
Sessione autunnale d'esame Sep 3, 2018 Sep 28, 2018
Degree sessions
Session From To
Sessione di laurea estiva Jul 18, 2018 Jul 18, 2018
Sessione di laurea autunnale Nov 22, 2018 Nov 22, 2018
Sessione di laurea invernale Mar 20, 2019 Mar 20, 2019
Holidays
Period From To
Christmas break Dec 22, 2017 Jan 7, 2018
Easter break Mar 30, 2018 Apr 3, 2018
Patron Saint Day May 21, 2018 May 21, 2018
Vacanze estive Aug 6, 2018 Aug 19, 2018

Exam calendar

Exam dates and rounds are managed by the relevant Science and Engineering Teaching and Student Services Unit.
To view all the exam sessions available, please use the Exam dashboard on ESSE3.
If you forgot your login details or have problems logging in, please contact the relevant IT HelpDesk, or check the login details recovery web page.

Exam calendar

Should you have any doubts or questions, please check the Enrolment FAQs

Academic staff

B C D F G M O P Q S T U V

Bicego Manuele

manuele.bicego@univr.it +39 045 802 7072
Foto,  February 9, 2017

Bloisi Domenico Daniele

domenico.bloisi@univr.it

Boscaini Maurizio

maurizio.boscaini@univr.it

Buffelli Mario Rosario

mario.buffelli@univr.it +39 0458027268

Busato Federico

federico.busato@univr.it

Calanca Andrea

andrea.calanca@univr.it +39 045 802 7847

Capaldi Stefano

stefano.capaldi@univr.it +39 045 802 7907

Castellini Alberto

alberto.castellini@univr.it +39 045 802 7908

Cicalese Ferdinando

ferdinando.cicalese@univr.it +39 045 802 7969

Combi Carlo

carlo.combi@univr.it 045 802 7985

Daducci Alessandro

alessandro.daducci@univr.it +39 045 8027025

Delledonne Massimo

massimo.delledonne@univr.it 045 802 7962; Lab: 045 802 7058

Dell'Orco Daniele

daniele.dellorco@univr.it +39 045 802 7637

Dominici Paola

paola.dominici@univr.it 045 802 7966; Lab: 045 802 7956-7086

D'Onofrio Mariapina

mariapina.donofrio@univr.it 045 802 7801

Drago Nicola

nicola.drago@univr.it 045 802 7081

Farinelli Alessandro

alessandro.farinelli@univr.it +39 045 802 7842

Giachetti Andrea

andrea.giachetti@univr.it +39 045 8027998

Giorgetti Alejandro

alejandro.giorgetti@univr.it 045 802 7982

Gobbi Bruno

bruno.gobbi@univr.it

Gregorio Enrico

Enrico.Gregorio@univr.it 045 802 7937

Maris Bogdan Mihai

bogdan.maris@univr.it +39 045 802 7074

Menegaz Gloria

gloria.menegaz@univr.it +39 045 802 7024

Migliorini Sara

sara.migliorini@univr.it +39 045 802 7908

Oliboni Barbara

barbara.oliboni@univr.it +39 045 802 7077

Piccinelli Fabio

fabio.piccinelli@univr.it +39 045 802 7097

Posenato Roberto

roberto.posenato@univr.it +39 045 802 7967

Quaglia Davide

davide.quaglia@univr.it +39 045 802 7811

Spoto Nicola Fausto

fausto.spoto@univr.it +39 045 8027940

Trabetti Elisabetta

elisabetta.trabetti@univr.it 045/8027209

Villa Tiziano

tiziano.villa@univr.it +39 045 802 7034

Study Plan

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 enrolment year.

ModulesCreditsTAFSSD
6
A
(MAT/02)
6
C
(BIO/13)
12
C
(CHIM/03 ,CHIM/06)
6
A
(FIS/01)
ModulesCreditsTAFSSD
One course to be chosen among the following
2 courses to be chosen among the following
Other activitites
3
F
-
Final exam
3
E
-

1° Year

ModulesCreditsTAFSSD
6
A
(MAT/02)
6
C
(BIO/13)
12
C
(CHIM/03 ,CHIM/06)
6
A
(FIS/01)

3° Year

ModulesCreditsTAFSSD
One course to be chosen among the following
2 courses to be chosen among the following
Other activitites
3
F
-
Final exam
3
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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S00021

Credits

6

Scientific Disciplinary Sector (SSD)

MAT/06 - PROBABILITY AND STATISTICS

Language

Italian

The teaching is organized as follows:

Teoria

Credits

4

Period

II sem.

Academic staff

Bruno Gobbi, Bruno Gobbi

Laboratorio [Cognomi A-L]

Credits

2

Period

II sem.

Academic staff

Bruno Gobbi, Bruno Gobbi

Laboratorio [Cognomi M-Z]

Credits

2

Period

II sem.

Academic staff

Bruno Gobbi, Bruno Gobbi

Learning outcomes

The course aims to provide the basic concepts of descriptive Statistics and Probability, by modeling concrete problems through the use of probabilistic methods and, at the same time, to underline the natural application of these concepts to mathematical Statistics. The course also aims to provide actual tools to apply the main statistical techniques to real cases.
By the end of the course, students will have to show their knowledge and understanding of the main statistical techniques for the description and analysis of the phenomena under study; to express the ability to apply the acquired knowledge and understanding skills for the interpretation of the results of the applied statistical analyzes in a critical and proactive way, by using the available tools; to know how to develop the necessary skills to continue the studies independently in the field of statistical Analysis.

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.

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.

Bibliografia

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Teoria P. Baldi Calcolo delle Probabilità e Statistica (Edizione 2) Mc Graw-Hill 1998 8838607370
Teoria D. OLIVIERI Fondamenti di statistica Cedam, Padova  
Teoria D. OLIVIERI Temi svolti di statistica (2001-2007) Cedam, Padova 2008

Teaching materials

Type D and Type F activities

Modules not yet included

Career prospects


Module/Programme news

News for students

There you will find information, resources and services useful during your time at the University (Student’s exam record, your study plan on ESSE3, Distance Learning courses, university email account, office forms, administrative procedures, etc.). You can log into MyUnivr with your GIA login details.

Attendance

As stated in point 25 of the Teaching Regulations for the A.Y. 2021/2022, attendance at the course of study is not mandatory.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Graduation

List of theses and work experience proposals

Stage Research area
Correlated mutations Various topics

Gestione carriere


Further services

I servizi e le attività di orientamento sono pensati per fornire alle future matricole gli strumenti e le informazioni che consentano loro di compiere una scelta consapevole del corso di studi universitario.