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. 2021/2022

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
primo semestre (lauree) Sep 20, 2021 Jan 14, 2022
Periodo generico Oct 1, 2021 May 31, 2022
secondo semestre (lauree) Feb 21, 2022 Jun 1, 2022
Exam sessions
Session From To
sessione invernale Jan 17, 2022 Feb 18, 2022
sessione estiva Jun 6, 2022 Jul 8, 2022
sessione autunnale Aug 22, 2022 Sep 16, 2022
Degree sessions
Session From To
sessione autunnale (validità a.a. 2020/2021) Dec 6, 2021 Dec 10, 2021
sessione invernale (validità a.a. 2020/2021) Apr 6, 2022 Apr 8, 2022
sessione estiva (validità a.a. 2021/2022) Sep 5, 2022 Sep 6, 2022

Exam calendar

Exam dates and rounds are managed by the relevant Economics 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 G L M O P R S V

Bonfanti Angelo

angelo.bonfanti@univr.it 045 802 8292

Broglia Angela

angela.broglia@univr.it 045 802 8240

Brunetti Federico

federico.brunetti@univr.it 045 802 8494

Campedelli Bettina

bettina.campedelli@univr.it 045 802 8416

Campolmi Alessia

alessia.campolmi@univr.it 045 802 8071

Cicogna Veronica

veronica.cicogna@univr.it 045 802 8246

Confente Ilenia

ilenia.confente@univr.it 045 802 8174

De Mari Michele

michele.demari@univr.it 045 802 8226

Gaudenzi Barbara

barbara.gaudenzi@univr.it 045 802 8623

Lai Alessandro

alessandro.lai@univr.it 045 802 8574

Leardini Chiara

chiara.leardini@univr.it 045 802 8222

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Omodei Sale' Riccardo

riccardo.omodeisale@univr.it 045 802 8855

Pellegrini Letizia

letizia.pellegrini@univr.it 045 802 8345

Peretti Alberto

alberto.peretti@univr.it 0444 393936 (VI) 045 802 8238 (VR)

Rossignoli Cecilia

cecilia.rossignoli@univr.it 045 802 8173

Roveda Alberto

alberto.roveda@univr.it Dip. Sc. Ec. 045 802 8096 C.I.D.E. 045 8028084

Scricciolo Catia

catia.scricciolo@univr.it 045 802 8341

Simeoni Francesca

francesca.simeoni@univr.it + 39 045 802 8160

Stacchezzini Riccardo

riccardo.stacchezzini@univr.it 045 802 8186

Vannucci Virginia

virginia.vannucci@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
9
A
(IUS/01)
9
A
(SECS-P/01)
9
A
(SECS-S/06)
12
B
(SECS-P/08)
ModulesCreditsTAFSSD
9
B
(SECS-P/01)
1 MODULE TO BE CHOSEN BETWEEN THE FOLLOWING
1 MODULE TO BE CHOSEN BETWEEN THE FOLLOWING
6
B
(IUS/04)
1 MODULE TO BE CHOSEN BETWEEN THE FOLLOWING
9
B
(SECS-P/01)
9
B
(SECS-P/03)
6
F
(-)
Prova finale
3
E
(-)

1° Year

ModulesCreditsTAFSSD
9
A
(IUS/01)
9
A
(SECS-P/01)
9
A
(SECS-S/06)
12
B
(SECS-P/08)

2° Year

ModulesCreditsTAFSSD
9
B
(SECS-P/07)
9
B
(SECS-P/07)
9
B
(SECS-S/01)

3° Year

ModulesCreditsTAFSSD
9
B
(SECS-P/01)
1 MODULE TO BE CHOSEN BETWEEN THE FOLLOWING
1 MODULE TO BE CHOSEN BETWEEN THE FOLLOWING
6
B
(IUS/04)
1 MODULE TO BE CHOSEN BETWEEN THE FOLLOWING
9
B
(SECS-P/01)
9
B
(SECS-P/03)
6
F
(-)
Prova finale
3
E
(-)
Modules Credits TAF SSD
Between the years: 1°- 2°- 3°

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

4S00121

Coordinatore

Catia Scricciolo

Credits

9

Scientific Disciplinary Sector (SSD)

SECS-S/01 - STATISTICS

Language

Italian

Period

primo semestre (lauree) dal Sep 20, 2021 al Jan 14, 2022.

Learning outcomes

The course aims to provide the basic techniques of descriptive statistics, probability calculus and statistical inference for undergraduate students in business and economic sciences, who have acquired the necessary preliminary mathematical notions. Overall, these techniques provide the necessary toolkit for the quantitative analysis of processes related to the observation of collective phenomena. From a practical point of view, these techniques are necessary for descriptive, interpretative and decision-making purposes for conducting statistical surveys related to economic and social phenomena. In addition to providing the necessary mathematical statistics apparatus, the course aims at providing conceptual tools for a critical evaluation of the methodologies considered. At the end of the lessons, the student must be able to use the tools learned to conduct statistical analyses relating to economic and social phenomena.

Program

a) DESCRIPTIVE STATISTICS

• Data collection and classification; data types.

• Frequency distributions; histograms and charts.

• Measures of central tendency; arithmetic mean, geometric mean and harmonic mean; median; quartiles and
percentiles.

• Variability and measures of dispersion; variance and standard deviation; coefficient of variation.

• Moments; indices of skewness and kurtosis.

• Multivariate distributions; scatterplots; covariance; variance of the sum of more variables.

• Multivariate frequency distributions; conditional distributions; chi-squared index of dependence; Simpson’s
paradox.

• Method of least squares; least-squares regression line; Pearson’s coefficient of linear correlation; Cauchy-Schwarz
inequality; R^2 coefficient; total, explained and residual deviance.


b) PROBABILITY

• Random experiments; sample space; random events and operations; combinatorics.

• Conditional probability; independence; Bayes' theorem.

• Discrete and continuous random variables; distribution function; expectation and variance; Markov and
Tchebycheff's inequalities. Special discrete distributions: uniform, Bernoulli, Binomial, Poisson and geometric.
Special continuous distributions: continuous uniform, Gaussian, exponential.

• Multivariate discrete random variables; joint probability distribution; marginal and conditional probability
distributions; independence; covariance; correlation coefficient.

• Linear combinations of random variables; average of independent random variables; sum of independent, Gaussian
random variables.

• Weak law of large numbers; Bernoulli’s law of large numbers for relative frequencies; central limit theorem.


c) INFERENTIAL STATISTICS

• Sample statistics and sampling distributions; Chi-square distribution; Student's t distribution; Snedecor's F
distribution.

• Point estimates and estimators; unbiasedness, efficiency, consistency; estimate of a mean, of a proportion, of a
variance.

• Confidence intervals for a mean, for a proportion (large samples) and for a variance.

• Hypothesis testing; one and two tails tests for a mean, for a proportion (large samples) and for a variance;
hypothesis testing for differences between two means, two proportions (large samples) and two variances.



Textbooks

- A. AZZALINI (2001) Inferenza statistica: una presentazione basata sul concetto di verosimiglianza, 2nd Ed.,
Springer Verlag Italia.
- E. BATTISTINI (2004) Probabilità e statistica: un approccio interattivo con Excel. McGraw-Hill, Milano.
- S. BERNSTEIN, R. BERNSTEIN (2003) Statistica descrittiva, Collana Schaum's, numero 109. McGraw-Hill, Milano.
- S. BERNSTEIN, R. BERNSTEIN (2003) Calcolo delle probabilita', Collana Schaum's, numero 110. McGraw-Hill, Milano.
- S. BERNSTEIN, R. BERNSTEIN (2003) Statistica inferenziale, Collana Schaum's, numero 111. McGraw-Hill, Milano.
- F. P. BORAZZO, P. PERCHINUNNO (2007) Analisi statistiche con Excel. Pearson, Education.
- D. GIULIANI, M. M. DICKSON (2015) Analisi statistica con Excel. Maggioli Editore.
- P. KLIBANOFF, A. SANDRONI, B. MODELLE, B. SARANITI (2010) Statistica per manager, 1st Ed., Egea.
- D. M. LEVINE, D. F. STEPHAN, K. A. SZABAT (2014) Statistics for Managers Using Microsoft Excel, 7th Ed.,
Global Edition. Pearson.
- M. R. MIDDLETON (2004) Analisi statistica con Excel. Apogeo.
- D. PICCOLO (1998) Statistica, 2nd Ed. 2000. Il Mulino, Bologna.
- D. PICCOLO (2010) Statistica per le decisioni, New Ed. Il Mulino, Bologna.


Teaching methods

Course load is equal to 84 hours: the course consists of 48 lecture hours (equal to 6 ECTS credits) and of 36 exercise hours (equal to 3 ECTS credits).


Study Guide

A detailed syllabus will be made available at the end of the course on the e-learning platform.


Prerequisites

Students are supposed to have acquired math knowledge of basic concepts like limit, derivative and integral.


Exercise sessions

Exercise sessions are integral part of the course and necessary to adequate understanding of the topics.


Tutoring activities

There will be optional tutoring hours devoted to exercises during the course and before exam sessions. More detailed information will be made available in due course.

Bibliografia

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Examination Methods

The exam can be passed through two partial written tests or one general written test.


Contents, assessment methods and criteria for partial written tests

The first partial written test focuses on the part of the program explained until the break at the end of October, typically on Descriptive Statistics and part of Probability (cf. the program of the course). The second partial written test focuses on the rest of the program. The topics of the program on which each partial written test is based will be defined in detail in due course. The bonus earned by the student when passing the first partial written test can be used to access the second partial written test in ONLY ONE of the two exam sessions of January and February. In case of

- student's withdrawal during the second partial written test
- failing of the second partial written test
- failing of the total exam due to a final exam grade less than 18/30 (cf. assessment methods and criteria for partial written tests)

the exam can be subsequently taken ONLY through a general written test.

Both partial written tests include exercises and theoretical questions. Each partial written test is passed if the score is greater than or equal to 15/30. If both partial written tests are passed, the final exam mark results from the weighted average (eventually rounded up to the least greater integer) of the grades obtained in the single partial written tests. The exam is passed if this average is greater than or equal to 18/30. If the total score obtained is greater than or equal to 15 and less than 18, the student may take an additional oral test. There is the possibility to take an optional oral test for those who have obtained a score greater than or equal to 18/30. Date and time of the oral test will be promptly communicated after the written test.


Contents, assessment methods and criteria for general written test

The general written test covers all topics of the program and includes exercises and theoretical questions. The exam is passed if the score is greater than or equal to 18/30. If the grade earned is greater than or equal to 15 and less than 18, the student may take an additional oral test. There is the possibility to take an optional oral test for those who have obtained a score greater than or equal to 18/30. Date and time of the oral test will be promptly communicated after the written test.

Contents, assessment methods and criteria are the same for attending and non-attending students.

Type D and Type F activities

Nei piani didattici di ciascun Corso di studio è previsto l’obbligo di conseguire un certo numero di crediti formativi mediante attività a scelta (chiamate anche "di tipologia D e F").

Oltre che in insegnamenti previsti nei piani didattici di altri corsi di studio e in certificazioni linguistiche o informatiche secondo quanto specificato nei regolamenti di ciascun corso, tali attività possono consistere anche in iniziative extracurriculari di contenuto vario, quali ad esempio la partecipazione a un seminario o a un ciclo di seminari, la frequenza di laboratori didattici, lo svolgimento di project work, stage aggiuntivo, eccetera.

Come per ogni altra attività a scelta, è necessario che anche queste non costituiscano un duplicato di conoscenze e competenze già acquisite dallo studente.

Quelle elencate in questa pagina sono le iniziative extracurriculari che sono state approvate dal Consiglio della Scuola di Economia e Management e quindi consentono a chi vi partecipa l'acquisizione dei CFU specificati, alle condizioni riportate nelle pagine di dettaglio di ciascuna iniziativa.

Si ricorda in proposito che:
- tutte queste iniziative richiedono, per l'acquisizione dei relativi CFU, il superamento di una prova di verifica delle competenze acquisite, secondo le indicazioni contenute nella sezione "Modalità d'esame" della singola attività;
- lo studente è tenuto a inserire nel proprio piano degli studi l'attività prescelta e a iscriversi all'appello appositamente creato per la verbalizzazione, la cui data viene stabilita dal docente di riferimento e pubblicata nella sezione "Modalità d'esame" della singola attività.

COMPETENZE TRASVERSALI
Scopri i percorsi formativi promossi dal  Teaching and learning centre dell'Ateneo, destinati agli studenti iscritti ai corsi di laurea, volti alla promozione delle competenze trasversali: https://talc.univr.it/it/competenze-trasversali

ATTENZIONE: Per essere ammessi a sostenere una qualsiasi attività didattica, inlcuse quelle a scelta, è necessario essere iscritti all'anno di corso in cui essa viene offerta. Si raccomanda, pertanto, ai laureandi delle sessioni di dicembre e aprile di NON svolgere attività extracurriculari del nuovo anno accademico, cui loro non risultano iscritti, essendo tali sessioni di laurea con validità riferita all'anno accademico precedente. Quindi, per attività svolte in un anno accademico cui non si è iscritti, non si potrà dar luogo a riconoscimento di CFU.

primo semestre (lauree) From 9/20/21 To 1/14/22
years Modules TAF Teacher
1° 2° Marketing plan D Virginia Vannucci (Coordinatore)
Periodo generico From 10/1/21 To 5/31/22
years Modules TAF Teacher
1° 2° English for Business and Economics - Bachelor's Degrees D Marco Minozzo (Coordinatore)
1° 2° Data Analysis Laboratory with R (Verona) D Marco Minozzo (Coordinatore)
1° 2° Data Visualization Laboratory D Marco Minozzo (Coordinatore)
1° 2° Python Laboratory D Marco Minozzo (Coordinatore)
1° 2° Data Science Laboratory with SAP D Marco Minozzo (Coordinatore)
1° 2° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° Programming in Matlab D Marco Minozzo (Coordinatore)
1° 2° Programming in SAS D Marco Minozzo (Coordinatore)
1° 2° Samsung Innovation Camp D Marco Minozzo (Coordinatore)
secondo semestre (lauree) From 2/21/22 To 6/1/22
years Modules TAF Teacher
1° 2° AN INTRODUCTION TO LATEX TYPESETTING SYSTEM D Alberto Peretti (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° What paradigms beyond the pandemic? Individual vs. Society, Private vs. Public D Federico Brunetti (Coordinatore)

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.

Linguistic training CLA


Student mentoring


Graduation


Internships


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.