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. 2017/2018

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 Triennali Sep 18, 2017 Jan 12, 2018
Secondo Semestre Triennali Feb 19, 2018 Jun 1, 2018
Corsi intensivi estivi (Alba di Canazei) Jul 9, 2018 Aug 3, 2018
Exam sessions
Session From To
Prove Parziali Primo Semestre Nov 6, 2017 Nov 10, 2017
Esami Sessione Invernale triennali 2017 Jan 15, 2018 Feb 16, 2018
Prove Parziali Secondo Semestre Apr 9, 2018 Apr 13, 2018
Esami sessione estiva triennali 2018 Jun 4, 2018 Jul 6, 2018
Esami sessione autunnale 2018 Aug 27, 2018 Sep 14, 2018
Degree sessions
Session From To
Lauree sessione autunnale (validità a.a. 2016/17) Nov 27, 2017 Nov 28, 2017
Lauree sessione invernale (validità a.a. 2016/17) Apr 4, 2018 Apr 6, 2018
Lauree sessione estiva (validità a.a. 2017/18) Sep 10, 2018 Sep 11, 2018
Holidays
Period From To
Ognissanti Nov 1, 2017 Nov 1, 2017
Festa Immacolata Concezione Dec 8, 2017 Dec 8, 2017
attività sospese (Natale) Dec 23, 2017 Jan 7, 2018
Easter break Mar 30, 2018 Apr 3, 2018
Liberation Day Apr 25, 2018 Apr 25, 2018
attività sospese (Festa dei lavoratori) Apr 30, 2018 Apr 30, 2018
Festa dei lavoratori May 1, 2018 May 1, 2018
Festa Patronale May 21, 2018 May 21, 2018
attività sospese estive Aug 6, 2018 Aug 24, 2018

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 N O P R S T Z

Baccarani Claudio

claudio.baccarani@univr.it

Bonfanti Angelo

angelo.bonfanti@univr.it 045 802 8292

Borello Giuliana

giuliana.borello@univr.it 045 802 8273

Broglia Angela

angela.broglia@univr.it 045 802 8240

Campedelli Bettina

bettina.campedelli@univr.it 045 802 8416

Campolmi Alessia

alessia.campolmi@univr.it 045 802 8071

Cantele Silvia

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

Caprara Andrea

andrea.caprara@univr.it 39 045 8028819

Colombo Valentina

valentina.colombo@univr.it +39 0458028768

De Crescenzo Veronica

veronica.decrescenzo@univr.it 045 802 8163

De Mari Michele

michele.demari@univr.it 045 802 8226

Faccincani Lorenzo

lorenzo.faccincani@univr.it 045 802 8610

Gaudenzi Barbara

barbara.gaudenzi@univr.it 045 802 8623

Guiglia Giovanni

giovanni.guiglia@univr.it 045 802 8225

Lai Alessandro

alessandro.lai@univr.it 045 802 8574

Levati Maria Vittoria

vittoria.levati@univr.it 045 802 8640

Marangoni Giandemetrio

giandemetrio.marangoni@univr.it 045 8028193

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Mion Giorgio

giorgio.mion@univr.it 045.802 8172

Nardi Chiara

chiara.nardi@univr.it +39 045 8028768

Noto Sergio

elefante@univr.it 045 802 8008

Omodei Sale' Riccardo

riccardo.omodeisale@univr.it 045 802 8855

Ortoleva Maria Grazia

mariagrazia.ortoleva@univr.it 045 802 8052

Pellegrini Letizia

letizia.pellegrini@univr.it 045 802 8345

Rodean Neliana Ramona

neliana.rodean@univr.it +39 045/8028225

Rossi Francesco

francesco.rossi@univr.it 045 8028067

Rossignoli Cecilia

cecilia.rossignoli@univr.it 045 802 8173

Scricciolo Catia

catia.scricciolo@univr.it 045 802 8341

Stacchezzini Riccardo

riccardo.stacchezzini@univr.it 045 802 8186

Tondini Giovanni

giovanni.tondini@univr.it Verona: 045 8425449, Vicenza: 0444 393930

Torsello Marco

marco.torsello@univr.it +39 045 8028881

Zoli Claudio

claudio.zoli@univr.it 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 enrolment year.

ModulesCreditsTAFSSD
9
A
(IUS/01)
9
B
(SECS-P/08)
6
C
(IUS/09)
9
A
(SECS-P/01)
9
A
(SECS-S/06)
English language (B1 level)
6
E/F
-
ModulesCreditsTAFSSD
9
B
(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
9
B
(SECS-P/01)
6
B
(SECS-P/08)
6
C
(SECS-P/10)
Stage
6
S
-
Final exam
3
E
-

1° Year

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

2° Year

ModulesCreditsTAFSSD
9
B
(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
9
B
(SECS-P/01)
6
B
(SECS-P/08)
6
C
(SECS-P/10)
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

Catia Scricciolo

Credits

9

Scientific Disciplinary Sector (SSD)

SECS-S/01 - STATISTICS

Language

Italian

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.

Bibliografia

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.

Type D and Type F activities

List of courses with unassigned period
years Modules TAF Teacher
1° 2° 3° Advanced Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Excel Laboratory (Verona) D Marco Minozzo (Coordinatore)
1° 2° 3° Business Ethics Seminar D Renzo Beghini (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.

Gestione carriere


Area riservata studenti


Student mentoring


Graduation

List of theses and work experience proposals

theses proposals Research area
Proposte di tesi triennali Various topics

Internships


Linguistic training CLA


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.