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 triennali Sep 19, 2016 Jan 13, 2017
secondo semestre triennali Feb 20, 2017 Jun 1, 2017
Exam sessions
Session From To
Prove intermedie primo semestre Nov 7, 2016 Nov 11, 2016
Appelli esami sessione invernale Jan 16, 2017 Feb 17, 2017
Prove intermedie secondo semestre Apr 10, 2017 Apr 13, 2017
Appelli esami sessione estiva Jun 5, 2017 Jul 7, 2017
Appelli esami sessione autunnale Aug 28, 2017 Sep 15, 2017
Degree sessions
Session From To
Sessione autunnale Nov 30, 2016 Dec 1, 2016
Sessione invernale Apr 5, 2017 Apr 7, 2017
Sessione estiva Sep 11, 2017 Sep 13, 2017
Holidays
Period From To
Vacanze natalizie Dec 23, 2016 Jan 5, 2017
Vacanze pasquali Apr 14, 2017 Apr 18, 2017
Vacanze estive Aug 7, 2017 Aug 25, 2017

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 N O P R S T Z

Baccarani Claudio

symbol email claudio.baccarani@univr.it

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

Broglia Angela

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

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

Cantele Silvia

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

Caprara Andrea

symbol email andrea.caprara@univr.it symbol phone-number 39 045 8425319

Colombo Valentina

symbol email valentina.colombo@univr.it symbol phone-number +39 0458028768

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

Gamba Simona

symbol email simona.gamba@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

Levati Maria Vittoria

symbol email vittoria.levati@univr.it symbol phone-number 045 802 8640

Marangoni Giandemetrio

symbol email giandemetrio.marangoni@univr.it symbol phone-number 045 8028736

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

Nardi Chiara

symbol email chiara.nardi@univr.it symbol phone-number +39 045 8028768

Noto Sergio

symbol email sergio.noto@univr.it symbol phone-number 045 802 8008

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

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

Stacchezzini Riccardo

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

Tondini Giovanni

symbol email giovanni.tondini@univr.it symbol phone-number Verona: 045 8425449, Vicenza: 0444 393930

Torsello Marco

symbol email marco.torsello@univr.it symbol phone-number +39 045 8425381

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
9
A
SECS-S/06
6
C
IUS/09
9
A
SECS-P/01

2° Year  activated in the A.Y. 2017/2018

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. 2018/2019

ModulesCreditsTAFSSD
6
B
SECS-P/08
Prova finale
3
E
-
ModulesCreditsTAFSSD
9
A
IUS/01
9
A
SECS-S/06
6
C
IUS/09
9
A
SECS-P/01
activated in the A.Y. 2017/2018
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. 2018/2019
ModulesCreditsTAFSSD
6
B
SECS-P/08
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.




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

Primo Semestre Triennali dal Sep 18, 2017 al Jan 12, 2018.

Learning outcomes

The course aims at providing 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

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 focuses on all of the 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
Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinator)
Excel Laboratory (Verona) D Marco Minozzo (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