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.
Academic calendar
The academic calendar shows the deadlines and scheduled events that are relevant to students, teaching and technicaladministrative 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.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period  From  To 

I semestre  Oct 1, 2019  Jan 31, 2020 
II semestre  Mar 2, 2020  Jun 12, 2020 
Session  From  To 

Sessione invernale d'esame  Feb 3, 2020  Feb 28, 2020 
Sessione estiva d'esame  Jun 15, 2020  Jul 31, 2020 
Sessione autunnale d'esame  Sep 1, 2020  Sep 30, 2020 
Session  From  To 

Sessione Estiva  Jul 15, 2020  Jul 15, 2020 
Sessione Autunnale  Oct 16, 2020  Oct 16, 2020 
Sessione Autunnale Dicembre  Dec 11, 2020  Dec 11, 2020 
Sessione Invernale  Mar 17, 2021  Mar 17, 2021 
Period  From  To 

Festa di Ognissanti  Nov 1, 2019  Nov 1, 2019 
Festa dell'Immacolata  Dec 8, 2019  Dec 8, 2019 
Vacanze di Natale  Dec 23, 2019  Jan 6, 2020 
Vacanze di Pasqua  Apr 10, 2020  Apr 14, 2020 
Festa della Liberazione  Apr 25, 2020  Apr 25, 2020 
Festa del Lavoro  May 1, 2020  May 1, 2020 
Festa del Santo Patrono  May 21, 2020  May 21, 2020 
Festa della Repubblica  Jun 2, 2020  Jun 2, 2020 
Vacanze estive  Aug 10, 2020  Aug 23, 2020 
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.
Should you have any doubts or questions, please check the Enrolment FAQs
Academic staff
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.
Modules  Credits  TAF  SSD 

Modules  Credits  TAF  SSD 

Modules  Credits  TAF  SSD 

1° Year
Modules  Credits  TAF  SSD 

2° Year
Modules  Credits  TAF  SSD 

3° Year
Modules  Credits  TAF  SSD 

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.
Probability and Statistics (2019/2020)
Teaching code
4S00021
Credits
6
Coordinatore
Scientific Disciplinary Sector (SSD)
MAT/06  PROBABILITY AND STATISTICS
Language
Italian
The teaching is organized as follows:
Teoria
Credits
4
Period
II semestre
Academic staff
Silvia Francesca Storti
Laboratorio
Credits
2
Period
II semestre
Academic staff
Silvia Francesca Storti
Learning outcomes
The course aims at providing the fundamental concepts of descriptive statistics and probability, with the task of modeling real problems by means of probability methods and applying to real problems statistic techniques. At the end of the course the student will have to demonstrate to understand the main statistical techniques for describing problems; to be able to interpret results of statistical analyses; to be able to develop knowhow necessary to continue the study autonomously in the context of statistical analysis.
Program

MM: Teoria

(1) Descriptive Statistics. Describing data sets (frequency tables and graphs). Summarizing data sets (sample mean, median, and mode, sample variance and standard deviation, percentiles and box plots). Normal data sets. Sample correlation coefficient.
(2) Probability theory. Elements of probability: sample space and events, Venn diagrams and the algebra of events, axioms of probability, sample spaces having equally likely outcomes, conditional probability, Bayes’ formula, independent events. Random variables and expectation: types of random variables, expected value and properties, variance, covariance and variance of sums of random variables. Moment generating functions. Weak law of large numbers. Special random variables: special random variables and distributions arising from the normal (chisquare, t, F).
(3) Statistical inference. Distributions of sampling statistics. Parameter estimation (maximum likelihood estimators, interval estimates). Hypothesis testing and significance levels.
(4) Regression. Least squares estimators of the regression parameters. Distribution of the estimators. Statistical inferences about the regression parameters. The coefficient of determination and the sample correlation coefficient. Analysis of residuals: assessing the model. Transforming to linearity. Weighted least squares.

MM: Laboratorio

The course includes a series of laboratories in the computer lab with exercises in MATLAB environment. After an introduction to MATLAB and to the main functions and tools useful for statistics, some exercises will be proposed on descriptive statistics and probability; for computing the probability density function (pdf) and cumulative distribution function (cdf) of special random variables, for generating random data and estimating parameters; on hypothesis testing for distributions and linear regression. The laboratories complement lectures by consolidating learning and developing problemsolving and handson practical skills.
Teaching methods. Regular lectures with power point presentation and blackboard and laboratory exercises. Educational material will be available to students enrolled in the course on the Moodle platform. This material includes lecture presentations in PDF format and material related to laboratory activities. For further details and supplementary materials, please refer to the reference books.
Examination Methods
Written exam consisting of theoretical questions (test with multiple choice), problems, and laboratory questions (open questions).
To pass the exam, the students must show that:
 they have understood the basic concepts of probability theory and statistics;
 they are able to use the knowledge acquired during the course to solve the assigned problem;
 they are able to program in MATLAB environment in the statistical and probabilistic context.
Bibliografia
Activity  Author  Title  Publishing house  Year  ISBN  Notes 

Teoria  Sheldon M. Ross  Probabilità e Statistica per l'ingegneria e le scienze, Apogeo Education, terza edizione, 2015, ISBN: 9788891609946 (Edizione 3)  Apogeo Education  2015  9788891609946 
Type D and Type F activities
years  Modules  TAF  Teacher 

3°  The fashion lab (1 ECTS)  D 
Maria Caterina Baruffi
(Coordinatore)

years  Modules  TAF  Teacher 

3°  Python programming language  D 
Maurizio Boscaini
(Coordinatore)

years  Modules  TAF  Teacher 

3°  CyberPhysical Laboratory  D 
Andrea Calanca
(Coordinatore)

3°  C++ Programming Language  D 
Federico Busato
(Coordinatore)

3°  LaTeX Language  D 
Enrico Gregorio
(Coordinatore)

3°  MatlabSimulink programming  D 
Bogdan Mihai Maris
(Coordinatore)

years  Modules  TAF  Teacher 

3°  Corso Europrogettazione  D  Not yet assigned 
3°  The course provides an introduction to blockchain technology. It focuses on the technology behind Bitcoin, Ethereum, Tendermint and Hotmoka.  D 
Matteo Cristani

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.