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. 2019/2020

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..

Academic year:
Definition of lesson periods
Period From To
First semester bachelor degree Sep 16, 2019 Jan 10, 2020
Second semester bachelor degree Feb 17, 2020 Jun 5, 2020
Exam sessions
Session From To
First semester intermediate tests Nov 4, 2019 Nov 8, 2019
Winter exam session Jan 13, 2020 Feb 14, 2020
Second semester intermediate tests Apr 15, 2020 Apr 17, 2020
Summer session exam Jun 8, 2020 Jul 10, 2020
Autumn Session exams Aug 24, 2020 Sep 11, 2020
Degree sessions
Session From To
Autumn Session Dec 2, 2019 Dec 4, 2019
Winter Session Apr 7, 2020 Apr 9, 2020
Summer session Sep 7, 2020 Sep 9, 2020

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 F G L M P R S

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

Bucciol Alessandro

alessandro.bucciol@univr.it 045 802 8278

Cantele Silvia

silvia.cantele@univr.it 045 802 8220 (VR) - 0444 393943 (VI)

Chesini Giuseppina

giusy.chesini@univr.it 045 802 8495 (VR) -- 0444/393938 (VI)

Cipriani Giam Pietro

giampietro.cipriani@univr.it 045 802 8271

Confente Ilenia

ilenia.confente@univr.it 045 802 8174

Corbella Silvano

silvano.corbella@univr.it 045 802 8217

Corsi Corrado

corrado.corsi@univr.it 045 802 8452 (VR) 0444/393937 (VI)

Demo Edoardo

edoardo.demo@univr.it 045 802 8782 (VR) 0444.393930 (VI)

Ferrari Maria Luisa

marialuisa.ferrari@univr.it 045 802 8532

Giaretta Elena

elena.giaretta@univr.it 045 802 8051

Guiglia Giovanni

giovanni.guiglia@univr.it 045 802 8225

Lubian Diego

diego.lubian@univr.it 045 802 8419

Manzoni Elena

elena.manzoni@univr.it 8783

Mariutti Gianpaolo

gianpaolo.mariutti@univr.it 045 802 8241

Menon Martina

martina.menon@univr.it 045 802 8420

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Mion Giorgio

giorgio.mion@univr.it 045.802 8172

Pasquariello Federica

federica.pasquariello@univr.it 045 802 8233

Perali Federico

federico.perali@univr.it 045 802 8486

Pilati Andrea

andrea.pilati@univr.it 045 802 8444 (VR) - 0444 393938 (VI)

Pizzamiglio Maurizio

maurizio.pizzamiglio@univr.it

Renò Roberto

roberto.reno@univr.it 045 802 8526

Roveda Alberto

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

Salomoni Alessandra

alessandra.salomoni@univr.it 045 802 8443

Santi Flavio

flavio.santi@univr.it 045 802 8239

Sartori Fabio

fabio.sartori@univr.it

Signori Paola

paola.signori@univr.it 0444 393942 (VI) 045 802 8492 (VR)

Sommacal Alessandro

alessandro.sommacal@univr.it 045 802 8716

Sproviero Alice Francesca

alicefrancesca.sproviero@univr.it 045 802 8216

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
B
(SECS-P/08)
6
B
(IUS/09)
9
A
(SECS-P/01)
9
A
(SECS-S/06)
English language (B1 level)
6
E/F
-
ModulesCreditsTAFSSD
9
A
(IUS/04)
9
B
(SECS-P/01)
9
B
(SECS-P/07)
9
B
(SECS-P/07)
9
B
(SECS-P/03)
9
B
(SECS-S/01)
ModulesCreditsTAFSSD
6
B
(IUS/07)
9
C
(SECS-P/09)
9
B
(SECS-S/06)
9
B
(SECS-P/02)
9
C
(SECS-P/12)
Stage
6
S
-
Final exam
3
E
-

1° Year

ModulesCreditsTAFSSD
9
A
(IUS/01)
9
B
(SECS-P/08)
6
B
(IUS/09)
9
A
(SECS-P/01)
9
A
(SECS-S/06)
English language (B1 level)
6
E/F
-

2° Year

ModulesCreditsTAFSSD
9
A
(IUS/04)
9
B
(SECS-P/01)
9
B
(SECS-P/07)
9
B
(SECS-P/07)
9
B
(SECS-P/03)
9
B
(SECS-S/01)

3° Year

ModulesCreditsTAFSSD
6
B
(IUS/07)
9
C
(SECS-P/09)
9
B
(SECS-S/06)
9
B
(SECS-P/02)
9
C
(SECS-P/12)
Stage
6
S
-
Final exam
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

Marco Minozzo

Credits

9

Scientific Disciplinary Sector (SSD)

SECS-S/01 - STATISTICS

Language

Italian

Period

First semester bachelor degree dal Sep 16, 2019 al Jan 10, 2020.

Learning outcomes

This module provides the basic techniques of descriptive statistics, probability and statistical inference to undergraduate students in economic and business sciences. Prerequisite to the course is the mastering of a few basic mathematical concepts such as limit, derivative and integration at the level of an undergraduate first year introductory course in calculus. Overall, these techniques provide the necessary toolkit for quantitative analysis in the processes related to the observation and understanding of collective phenomena. From a practical point of view, they are necessary for descriptive, interpretative and decision-making purposes and for conducting statistical studies related to economic and social phenomena. In addition to providing the necessary mathematical apparatus, the course also aims at providing the conceptual tools for a critical evaluation of the methodologies considered.

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.
• Fixed-base indices and chain indices; Laspayres and Paasche indices.
• 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; index of association C; Simpson’s paradox.
• Method of least squares; least-squares regression line; Pearson’s coefficient of linear correlation r; Cauchy-Schwarz inequality; R-square coefficient; explained deviance and residual deviance.

b) Probability

• Random events; algebras and sigma-algebras; probability spaces and event trees; combinatorics.
• Conditional probability; independence; Bayes theorem.
• Discrete and continuous random variables; distribution function; expectation and variance; Markov and Chebyshev inequalities.
• Discrete uniform distributions; Bernoulli distribution; binomial distribution; Poisson distribution; geometric distribution.
• Continuous uniform distributions; normal distribution; exponential distribution.
• 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 and 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-t distribution; Snedecors-F distribution.
• Point estimates and estimators; unbiasedness; efficiency; consistency; estimate of the mean, of a proportion and of a variance.
• Confidence intervals for a mean, for a proportion (large samples) and for a variance.
• Hypothesis testing; power and observed significance level; one and two tails tests for a mean, for a proportion (large samples) and for a variance; hypothesis testing for differences in two means, two proportions (large samples) and two variances.

Textbook

- G. CICCHITELLI, P. D’URSO, M. MINOZZO (2018), Statistica: principi e metodi, Terza edizione, Pearson Italia, Milano.

Reading list

- A. AZZALINI (2001), Inferenza statistica: una presentazione basata sul concetto di verosimiglianza, Seconda edizione. 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 probabilità, 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, Prima edizione, Egea.
- D. M. LEVINE, D. F. STEPHAN, K. A. SZABAT (2014), Statistics for Managers Using Microsoft Excel, Seventh Edition, Global Edition. Pearson.
- M. R. MIDDLETON (2004), Analisi statistica con Excel. Apogeo.
- D. PICCOLO (1998), Statistica, Seconda edizione 2000. Il Mulino, Bologna.
- D. PICCOLO (2010), Statistica per le decisioni, Nuova edizione. Il Mulino, Bologna.

Study guide

Detailed indications, regarding the use of the textbook, will be given during the course. Supporting material (written records of the lessons, exercises with solutions, past exam papers with solutions, etc.) is available on the E-learning platform of the University.

Prerequisites

Students are supposed to have acquired mathematical knowledge of basic concepts such as limit, derivative and integral.

Teaching methods

Course load is equal to 84 hours. All classes are essential to a proper understanding of the topics of the course. The working language is Italian.

Exercise sessions

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

Tutoring activities

In addition to lessons and exercise hours, before each exam session there will be tutoring hours devoted to revision. More detailed information will be available during the course.

Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
D. Giuliani, M. M. Dickson Analisi statistica con Excel Maggioli Editore 2015 8838789908
M. R. Middleton Analisi statistica con Excel Apogeo, Milano 2004
F. P. Borazzo, P. Perchinunno Analisi statistiche con Excel Pearson, Education 2007
S. Bernstein, R. Bernstein Calcolo delle Probabilita', Collana Schaum's, numero 110. McGraw-Hill, Milano 2003
A. Azzalini Inferenza Statistica: Una presentazione basata sul concetto di verosimiglianza (Edizione 2) Springer Verlag Italia 2001 9788847001305 Laurea in Matematica Applicata
E. Battistini Probabilità e statistica: un approccio interattivo con Excel McGraw-Hill, Milano 2004
D. Piccolo Statistica Il Mulino 2000 8815075968
S. Bernstein, R. Bernstein Statistica descrittiva, Collana Schaum's, numero 109 McGraw-Hill, Milano 2003
S. Bernstein, R. Bernstein Statistica inferenziale, Collana Schaum's, numero 111. McGraw-Hill, Milano 2003
D. Piccolo Statistica per le decisioni Il Mulino 2004 8815097708
P. Klibanoff, A. Sandroni, B. Moselle, B. Saraniti Statistica per manager (Edizione 1) Egea 2010 9788823821347
G. Cicchitelli, P. D'Urso, M. Minozzo Statistica: principi e metodi (Edizione 3) Pearson Italia, Milano 2018 9788891902788 Libro di testo
D. M. Levine, D. F. Stephan, K. A. Szabat Statistics for Managers Using Microsoft Excel, Global Edition (Edizione 7) Pearson 2014 0133061817

Examination Methods

The final exam consists of a written test (of two hours and 30 minutes) with classical exercises and multiple choice questions. For the written test, students can use a scientific calculator; any other material (books, notes, etc.) is forbidden. To pass the exam, students must receive at least 15 out of 30 in both parts of the written test. If the final mark (that is the average of the grades obtained in the two parts of the written test) is less the 18 out of 30, the student is required to sit for an oral examination. Contents, assessment methods and criteria are the same for all students and do not depend on the number of classes attended.

A noncompulsory intermediate test on the first part of the program (typically on descriptive statistics and a part of probability) is planned for the beginning of November. The passing of this intermediate test can entail an increase of at most three points of the result obtained in the written test (if the written test is taken and passed in one of the two winter examination sessions).

Teaching materials

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.

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.

Academic year:
Second semester bachelor degree From 2/17/20 To 6/5/20
years Modules TAF Teacher
1° 2° 3° Enactus Verona 2020 D Paola Signori (Coordinatore)
1° 2° 3° Parlare in pubblico e economic writing D Martina Menon (Coordinatore)
1° 2° 3° Samsung Innovation Camp D Marco Minozzo (Coordinatore)
1° 2° 3° Simulation and Implementation of Economic Policies D Federico Perali (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° 3° Il Futuro Conta! D Alessandro Bucciol (Coordinatore)
1° 2° 3° Il Futuro Conta! D Alessandro Bucciol (Coordinatore)
1° 2° 3° Data Analysis Laboratory with R D Marco Minozzo (Coordinatore)
1° 2° 3° Data Analysis Laboratory with R (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Data Visualization Laboratory D Marco Minozzo (Coordinatore)
1° 2° 3° Python Laboratory D Marco Minozzo (Coordinatore)
1° 2° 3° Data Science Laboratory with SAP D Marco Minozzo (Coordinatore)
1° 2° 3° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° The fashion lab (1 ECTS) D Angela Broglia (Coordinatore)
1° 2° 3° The fashion lab (2 ECTS) D Angela Broglia (Coordinatore)
1° 2° 3° The fashion lab (3 ECTS) D Angela Broglia (Coordinatore)
1° 2° 3° Marketing Plan D Ilenia Confente (Coordinatore)
1° 2° 3° Presente e futuro del pianeta D Federico Brunetti (Coordinatore)
1° 2° 3° Programming in Matlab D Marco Minozzo (Coordinatore)
1° 2° 3° Programming in SAS D Marco Minozzo (Coordinatore)
1° 2° 3° Robo-Ethics D Giorgio Mion (Coordinatore)
1° 2° 3° Univero' - Job Orienteering festival D Paola Signori (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.

Student mentoring


Linguistic training CLA


Internships


Gestione carriere


Graduation

List of theses and work experience proposals

theses proposals Research area
Tesi di laurea - Il credit scoring Statistics - Foundational and philosophical topics
La performance delle imprese che adottano politiche di Corporate Social responsibility Various topics
La previsione della qualita' dei vini: Il caso dell'Amarone Various topics
Proposte di tesi Various topics
Tesi in Macroeconomia Various topics
tesi triennali Various topics

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.