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 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
primo semestre lauree triennali Sep 17, 2018 Jan 11, 2019
secondo semestre lauree triennali Feb 18, 2019 May 31, 2019
Exam sessions
Session From To
prove intermedie - sessione autunnale Nov 5, 2018 Nov 9, 2018
sessione invernale lauree triennali Jan 14, 2019 Feb 15, 2019
prove intermedie - sessione primaverile Apr 15, 2019 Apr 18, 2019
sessione estiva lauree triennali Jun 3, 2019 Jul 5, 2019
Sessione autunnale Aug 26, 2019 Sep 13, 2019
Degree sessions
Session From To
Sessione autunnale (validità a.a. 2017/18) Dec 6, 2018 Dec 7, 2018
Sessione invernale (validità a.a. 2017/18) Apr 3, 2019 Apr 5, 2019
Sessione estiva (validità a.a. 2018/19) Sep 10, 2019 Sep 11, 2019
Holidays
Period From To
Festa di Ognissanti Nov 1, 2018 Nov 1, 2018
Festa dell’Immacolata Dec 8, 2018 Dec 8, 2018
Vacanze di Natale Dec 22, 2018 Jan 6, 2019
Vacanze di Pasqua Apr 19, 2019 Apr 23, 2019
Festa della liberazione Apr 25, 2019 Apr 25, 2019
Festa del lavoro May 1, 2019 May 1, 2019
Festa del Santo Patrono - S. Zeno May 21, 2019 May 21, 2019
Attività sospese (vacanze estive) Aug 5, 2019 Aug 23, 2019

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 Enrollment FAQs

Academic staff

B C D F G L M O P R S Z

Bertoli Paola

symbol email paola.bertoli@univr.it symbol phone-number 045 8028 508

Bonfanti Angelo

symbol email angelo.bonfanti@univr.it symbol phone-number 045 802 8292
Foto profilo,  September 20, 2017

Borello Giuliana

symbol email giuliana.borello@univr.it symbol phone-number 045 802 8493

Bracco Emanuele

symbol email emanuele.bracco@univr.it symbol phone-number 045 802 8293

Broglia Angela

symbol email angela.broglia@univr.it symbol phone-number 045 802 8240

Brunetti Federico

symbol email federico.brunetti@univr.it symbol phone-number 045 802 8494

Bucciol Alessandro

symbol email alessandro.bucciol@univr.it symbol phone-number 045 802 8278

Campedelli Bettina

symbol email bettina.campedelli@univr.it symbol phone-number 045 802 8416

Campolmi Alessia

symbol email alessia.campolmi@univr.it symbol phone-number 045 802 8071

Confente Ilenia

symbol email ilenia.confente@univr.it symbol phone-number 045 802 8174

De Crescenzo Veronica

symbol email veronica.decrescenzo@univr.it symbol phone-number 045 802 8163

De Mari Michele

symbol email michele.demari@univr.it symbol phone-number 045 802 8226

Faccincani Lorenzo

symbol email lorenzo.faccincani@univr.it symbol phone-number 045 802 8610

Gatti Stefano

symbol email stefano.gatti@univr.it

Gaudenzi Barbara

symbol email barbara.gaudenzi@univr.it symbol phone-number 045 802 8623

Guiglia Giovanni

symbol email giovanni.guiglia@univr.it symbol phone-number 045 802 8225

Lai Alessandro

symbol email alessandro.lai@univr.it symbol phone-number 045 802 8574

Leardini Chiara

symbol email chiara.leardini@univr.it symbol phone-number 045 802 8222

Levati Maria Vittoria

symbol email vittoria.levati@univr.it symbol phone-number 045 802 8640
Elena Manzoni,  February 4, 2020

Manzoni Elena

symbol email elena.manzoni@univr.it symbol phone-number 8783

Matteazzi Eleonora

symbol email eleonora.matteazzi@univr.it symbol phone-number 045 8028741

Menon Martina

symbol email martina.menon@univr.it symbol phone-number 045 8028420

Minozzo Marco

symbol email marco.minozzo@univr.it symbol phone-number 045 802 8234

Mion Giorgio

symbol email giorgio.mion@univr.it symbol phone-number 045.802 8172

Omodei Sale' Riccardo

symbol email riccardo.omodeisale@univr.it symbol phone-number 045 8425355

Ortoleva Maria Grazia

symbol email mariagrazia.ortoleva@univr.it symbol phone-number 045 802 8052

Pellegrini Letizia

symbol email letizia.pellegrini@univr.it symbol phone-number 045 802 8345

Perali Federico

symbol email federico.perali@univr.it symbol phone-number 045 802 8486

Rossi Francesco

symbol email francesco.rossi@univr.it symbol phone-number 045 8028067

Rossignoli Cecilia

symbol email cecilia.rossignoli@univr.it symbol phone-number 045 802 8173

Scricciolo Catia

symbol email catia.scricciolo@univr.it symbol phone-number 045 8028341

Signori Paola

symbol email paola.signori@univr.it symbol phone-number 0458028492

Stacchezzini Riccardo

symbol email riccardo.stacchezzini@univr.it symbol phone-number 0458028186

Zoli Claudio

symbol email claudio.zoli@univr.it symbol phone-number 045 802 8479

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 enrollment year.

1° Year

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

2° Year  activated in the A.Y. 2019/2020

ModulesCreditsTAFSSD
9
B
IUS/04
9
B
SECS-P/01
9
B
SECS-P/03
9
B
SECS-S/01

3° Year  activated in the A.Y. 2020/2021

ModulesCreditsTAFSSD
6
B
SECS-P/08
Stage
6
S
-
Final exam
3
E
-
ModulesCreditsTAFSSD
9
A
IUS/01
6
C
IUS/09
9
A
SECS-P/01
9
A
SECS-S/06
English language (B1 level)
6
E/F
-
activated in the A.Y. 2019/2020
ModulesCreditsTAFSSD
9
B
IUS/04
9
B
SECS-P/01
9
B
SECS-P/03
9
B
SECS-S/01
activated in the A.Y. 2020/2021
ModulesCreditsTAFSSD
6
B
SECS-P/08
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.




S Placements in companies, public or private institutions and professional associations

Teaching code

4S00121

Credits

9

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-S/01 - STATISTICS

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 for undergraduate students in business and economic sciences that have acquired the necessary preliminary mathematical notions. Overall, these techniques provide the necessary toolkit for quantitative analysis in the 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 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.

• 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 are necessary to adequate understanding of the topics.


Tutoring activities

There will be optional tutoring hours devoted to exercises before each exam session. More detailed information will be made available in due course.

Reference texts
Author Title Publishing house Year ISBN Notes
G. Cicchitelli, P. D'Urso, M. Minozzo Statistica: principi e metodi (Edizione 3) Pearson Italia, Milano 2018 9788891902788

Examination Methods

NOTICE: Due to the ongoing epidemic emergency, in the summer session of the a.y. 2019/2020, the examination procedure will be oral.


The exam can be passed through two partial written tests or a 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. 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 in 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.


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.

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

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE

Type D and Type F activities

Academic year:
List of courses with unassigned period
years Modules TAF Teacher
Business Ethics Seminar D Renzo Beghini (Coordinator)
SFIDE - Europe D Claudio Zoli (Coordinator)
1° 2° 3° Advanced risk and portfolio management bootcamp (online) (3 cfu) D Roberto Renò (Coordinator)
1° 2° 3° Advanced risk and portfolio management bootcamp (onsite) (6 cfu) D Roberto Renò (Coordinator)
1° 2° 3° Convegno "gli scambi commerciali con l'estero: questioni fiscali, doganali e contrattuali" D Sebastiano Maurizio Messina (Coordinator)
1° 2° 3° Ineka conference 2019 teamworking membership D Federico Brunetti (Coordinator)
1° 2° 3° Data Visualization Laboratory D Marco Minozzo (Coordinator)
1° 2° 3° Python Laboratory D Marco Minozzo (Coordinator)
1° 2° 3° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° 3° Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
1° 2° 3° "le grandi trasformazioni degli anni '60-'70 e l'italia cinquant'anni dopo" D Angelo Zago (Coordinator)
1° 2° 3° Social responsibility model for the restaurants' ecosystems D Silvia Cantele (Coordinator)
1° 2° 3° Marketing Plan D Ilenia Confente (Coordinator)
1° 2° 3° Polis - festival biblico in universita' D Giorgio Mion (Coordinator)
1° 2° 3° Quality and problem solving in business organizations D Paola Castellani (Coordinator)
1° 2° 3° La competitività regionale e le sue risorse endogene: il concetto di capitale territoriale D Riccardo Fiorentini (Coordinator)
1° 2° 3° Soft skills in action D Paola Signori (Coordinator)

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: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.

Graduation

List of thesis proposals

theses proposals Research area
Proposte di tesi triennali Various topics

Student mentoring


Linguistic training CLA


Gestione carriere


Internships

The curriculum of the three-year degree courses (CdL) and master's degree courses (CdLM) in the economics area includes an internship as a compulsory training activity. Indeed, the internship is considered an appropriate tool for acquiring professional skills and abilities and for facilitating the choice of a future professional outlet that aligns with one's expectations, aptitudes, and aspirations. The student can acquire further competencies and interpersonal skills through practical experience in a work environment.


Student login and resources