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. 2013/2014

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 semestre Oct 1, 2013 Jan 31, 2014
II semestre Mar 3, 2014 Jun 13, 2014
Exam sessions
Session From To
Sessione straordinaria Feb 3, 2014 Feb 28, 2014
Sessione estiva Jun 16, 2014 Jul 31, 2014
Sessione autunnale Sep 1, 2014 Sep 30, 2014
Degree sessions
Session From To
Sessione autunnale Oct 15, 2013 Oct 15, 2013
Sessione straordinaria Dec 9, 2013 Dec 9, 2013
Sessione invernale Mar 18, 2014 Mar 18, 2014
Sessione estiva Jul 21, 2014 Jul 21, 2014
Holidays
Period From To
Vacanze Natalizie Dec 22, 2013 Jan 6, 2014
Vacanze di Pasqua Apr 17, 2014 Apr 22, 2014
Festa del S. Patrono S. Zeno May 21, 2014 May 21, 2014
Vacanze Estive Aug 11, 2014 Aug 15, 2014

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

A B C D F G M O R S Z

Angeleri Lidia

lidia.angeleri@univr.it 045 802 7911

Baldo Sisto

sisto.baldo@univr.it 045 802 7935

Bos Leonard Peter

leonardpeter.bos@univr.it +39 045 802 7987

Caliari Marco

marco.caliari@univr.it +39 045 802 7904

Daldosso Nicola

nicola.daldosso@univr.it +39 045 8027076 - 7828 (laboratorio)

Di Persio Luca

luca.dipersio@univr.it +39 045 802 7968

Ferro Ruggero

ruggero.ferro@univr.it 045 802 7909

Guerriero Massimo

massimo.guerriero@univr.it

Magazzini Laura

laura.magazzini@univr.it 045 8028525

Malachini Luigi

luigi.malachini@univr.it 045 8054933

Mantese Francesca

francesca.mantese@univr.it +39 045 802 7978

Marigonda Antonio

antonio.marigonda@univr.it +39 045 802 7809

Mariotto Gino

gino.mariotto@univr.it +39 045 8027031

Mariutti Gianpaolo

gianpaolo.mariutti@univr.it 045 802 8241

Menon Martina

martina.menon@univr.it 045 802 8420

Morato Laura Maria

laura.morato@univr.it 045 802 7904

Orlandi Giandomenico

giandomenico.orlandi at univr.it 045 802 7986

Rizzi Romeo

romeo.rizzi@univr.it +39 045 8027088

Sansonetto Nicola

nicola.sansonetto@univr.it 049-8027932

Solitro Ugo

ugo.solitro@univr.it +39 045 802 7977
Marco Squassina,  January 5, 2014

Squassina Marco

marco.squassina@univr.it +39 045 802 7913

Zampieri Gaetano

gaetano.zampieri@univr.it +39 045 8027979

Zuccher Simone

simone.zuccher@univr.it

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)
Uno tra i seguenti insegnamenti
6
C
(SECS-P/01)
6
C
(FIS/01)
6
B
(MAT/03)
Uno tra i seguenti insegnamenti
6
C
(SECS-P/01)
6
B
(MAT/06)
ModulesCreditsTAFSSD
Uno o due insegnamenti tra i seguenti per un totale di 12 cfu
12
C
(SECS-S/06)
6
C
(MAT/07)
6
C
(SECS-P/05)
Prova finale
6
E
(-)

2° Year

ModulesCreditsTAFSSD
6
A
(MAT/02)
Uno tra i seguenti insegnamenti
6
C
(SECS-P/01)
6
C
(FIS/01)
6
B
(MAT/03)
Uno tra i seguenti insegnamenti
6
C
(SECS-P/01)
6
B
(MAT/06)

3° Year

ModulesCreditsTAFSSD
Uno o due insegnamenti tra i seguenti per un totale di 12 cfu
12
C
(SECS-S/06)
6
C
(MAT/07)
6
C
(SECS-P/05)
Prova finale
6
E
(-)
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°
Between the years: 1°- 2°- 3°
Ulteriori conoscenze
6
F
-

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

4S00254

Credits

6

Coordinatore

Laura Maria Morato

Scientific Disciplinary Sector (SSD)

MAT/06 - PROBABILITY AND STATISTICS

Language

Italian

The teaching is organized as follows:

Esercitazioni

Credits

1

Period

I semestre

Academic staff

Marco Caliari

Catene di Markov in tempo discreto

Credits

3

Period

I semestre

Academic staff

Laura Maria Morato

Analisi di serie temporali

Credits

2

Period

I semestre

Academic staff

Federico Di Palma

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Learning outcomes

Module 1 ( Discrete time Markov Chains )

Basics of the theory of discrete time Markov chain with finite or countable state space and examples of application.


Module 2 (Practice session of Stochastic systems)

Approximation and computation of invariant probabilities, Metropolis algorithm, simulation of queues and renewal processes with the use of Matlab.

Module 3 Introduction to Time Series analysis: the lessons aims to provide to the student a general framework to analyze time series as the outcome of a discrete time model fed by a white noise and an exogenous input. The lesson are completed by the use of a dedicated software in order to apply the theoretical aspects.

Program

Module 1
Markov chains with finite space state:
Definitions, transition matrix, transition probability in n steps, Chapman -Kolmogorov equation, finite joint densities, Canonocal space and Kolmogorov theorem (without proof).
State classification, invariant probabilities, Markov-Kakutani theorem, example of gambler's ruin, regular chains, criterion, limit probabilities and Markov theorem, reversible chains, Metropolis algorithm and Simulated annealing, numerical generation of a discrete random variable and algorithm for generation an omogeneus Markov chains with finite state space.

Markov chains with countable space state:
Equivalent definitions of transient and recurrent state, positive recurrence, periodicity, solidarity property, canonical decomposition of the state space, invariant measures, existence theorem, example of the unlimited random walk. Ergodicity and limit theorems.

Elements of Martingales associated to discrete time Markov chains:
Natural filtration, stopping times, conditional expectation given a random variable, strong Markov property, martingales. Optional stopping Theorem, example of gambler's ruin.

Module 2 Approximation and computation of invariant probabilities, Metropolis algorithm, simulation of queues with the use of Matlab.

Module 3 Elements of time series analysis :
Main scope of time series analysis: modelling, prediction and simulation.
Identification problem main components: a priori Knowledge, experiment design, goodness criteria, model, filtering and validation.
Model: main variables and correspondent schema. (AR, ARX, ARMA, output-error).
Goodness Criteria: least square, Maximum Likelihood, Maximum a posteriori.
Filtering: Linear parameter model, frequency filtering.
Matlab : main purpose and examples.

Examination Methods

Module 1 Oral exam

Module 2 Discussion of the solution of given homeworks.

Module 3 Written exam

Bibliografia

Reference texts
Activity Author Title Publishing house Year ISBN Notes
Analisi di serie temporali LJung System Identification, Theory for the User (Edizione 2) Prentice Hall PTR 1999

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, except for specific practical or lab activities, attendance is not mandatory. Regarding these activities, please see the web page of each module for information on the number of hours that must be attended on-site.
Please refer to the Crisis Unit's latest updates for the mode of teaching.

Graduation

Attachments

List of theses and work experience proposals

theses proposals Research area
Formule di rappresentazione per gradienti generalizzati Mathematics - Analysis
Formule di rappresentazione per gradienti generalizzati Mathematics - Mathematics
Mathematics Bachelor and Master thesis titles Various topics
Stage Research area
Internship proposals for students in mathematics 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.