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 Magistrali Oct 2, 2017 Dec 22, 2017
Secondo Semestre Magistrali Feb 26, 2018 May 25, 2018
Exam sessions
Session From To
Esami sessione invernale Magistrali Jan 8, 2018 Feb 23, 2018
Esami sessione estiva Magistrali May 28, 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
All Saints Day 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
Labour Day 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 M N P R S Z

Baccarani Claudio

claudio.baccarani@univr.it

Berton Marina

marina.berton@univr.it

Bonfanti Angelo

angelo.bonfanti@univr.it 045 802 8292

Brunetti Federico

federico.brunetti@univr.it 045 802 8494

Capitello Roberta

roberta.capitello@univr.it 045 802 8488

Castellani Paola

paola.castellani@univr.it 045 802 8127

Cavallo Daniela

daniela.cavallo@univr.it

Corbella Silvano

silvano.corbella@univr.it 045 802 8217

Dalla Rosa Elisa

elisa.dallarosa@univr.it

Ferrari Maria Luisa

marialuisa.ferrari@univr.it 045 802 8532

Gaeta Davide Nicola Vincenzo

davide.gaeta@univr.it 045 683 5632

Goldoni Giovanni

giovanni.goldoni@univr.it 045 802 8792

Grossi Luigi

luigi.grossi@univr.it 045 802 8247

Guerriero Massimo

massimo.guerriero@univr.it

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Mion Giorgio

giorgio.mion@univr.it 045.802 8172

Moggi Sara

sara.moggi@univr.it 045 802 8290

Noto Sergio

elefante@univr.it 045 802 8008

Rossi Stefano

stefano.rossi@univr.it

Russo Ivan

ivan.russo@univr.it 045 802 8161 (VR)

Secondulfo Domenico

domenico.secondulfo@univr.it - domenico.secondulfo3@gmail.com

Signori Paola

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

Stacchezzini Riccardo

riccardo.stacchezzini@univr.it 045 802 8186

Zardini Alessandro

alessandro.zardini@univr.it 045 802 8565

Zarri Luca

luca.zarri@univr.it 045 802 8101

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.

CURRICULUM TIPO:
ModulesCreditsTAFSSD
6
B
(SECS-P/01)
9
B
(SECS-S/03)
6
B
(SECS-P/12)
Stage
6
F
-

1° Year

ModulesCreditsTAFSSD
6
B
(SECS-P/01)
9
B
(SECS-S/03)
6
B
(SECS-P/12)
Stage
6
F
-
Modules Credits TAF SSD
Between the years: 1°- 2°

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

4S00522

Teacher

Luigi Grossi

Coordinatore

Luigi Grossi

Credits

9

Scientific Disciplinary Sector (SSD)

SECS-S/03 - ECONOMIC STATISTICS

Language

Italian

Period

Primo Semestre Magistrali dal Oct 2, 2017 al Dec 22, 2017.

Learning outcomes

During the course, the main sources of official data will be studied and the main sampling techniques analyzed. The liner regression model will be introduced as one of the main statistical tools to examine collected data and for sales forecasting. Students will be provided with the cutting-edge statistical theory on sampling and linear regression model. These tools will then be applied to carry out market research.

Program

1. Market research:
- Definitions, purposes and limits.
- Case studies related to market research
- Statistical methods for market research
- The main steps of a market survey.


2. Data sources for market surveys
- Primary and secondary data sources.
- Secondary data sources: internal and external
- Official statistical data.
- Main databases for marketing research(Infocamere, Cerved, AIDA, ecc.)
- Agency data (GfK-Eurisko, ACNielsen Italia)
- Panel surveys


3. Random and non-random sampling designs
- Review of estimation theory
- Definition of sampling design
- Random sampling designs
- Non-random sampling designs
- Sampling and non-sampling errors

4. Questionnaire construction and interviewing techniques.
- Self-administered questionnaires
- Assisted interview
- Computer-assisted personal interview
- Web interview

5. The regression model for marketing and sales forecasting
- Simple regression model: definition and hypotheses
- Parameter estimation and tests
- Residual analysis
- Goodness of fitting
- Estimation of trend using polynomial functions
- Polynomial degree choice
- Sales forecasting using the regression model


The interaction with students will be encouraged by discussing real business cases. Students are also expected to present short business cases through the solution of exercises. All slides projected during lessons will be made available on the e-learning platform before the beginning of the course. For this reason, students are strongly invited to register to the e-learning page of the course. Lectures will be recorded. Videos will be made available the next few days to allow students to revise or to attend lessons to which they have not been able to join directly. The availability of videos is also extended to all students who are unable to attend for work reasons or because they are abroad within the Erasmus program.


Suggested books
- Bassi F. (2009, I Ristampa), Analisi di mercato: Strumenti statistici per le decisioni di marketing (Edizione I), Carocci editore.
- Bracalente B. , M. Cossignani, A. Mulas (2009), Statistica Aziendale, McGraw-Hill.
- Biggeri Luigi , Matilde Bini , Alessandra Coli , Laura Grassini , M. Maltagliati (2017), Statistica per le decisioni aziendali. Ediz. mylab. Con eText, edito da Pearson Education Italia.



Bibliografia

Reference texts
Author Title Publishing house Year ISBN Notes
Francesca Bassi Analisi di mercato: Strumenti statistici per le decisioni di marketing (Edizione 2) Carocci editore 2009 978-88-430-4427-6 I ristampa
B. Bracalente, M. Cossignani, A. Mulas Statistica Aziendale McGraw-Hill 2009

Examination Methods

Both the student's preparation will be evaluated as well as its ability to interpret and evaluate the results of the analyses based on the topics taught during the course.

The written test is compulsory. The structure of the test is as follows:
- one open question (up to 10 points, out of 30),
- two numerical exercises (up to 20 points, out of 30). Data will be provided for the solution of real case-studies using the basic tools learned during classes.
The oral test is optional.

Optional activity (attending students only)
Every attending student is given the opportunity to solve an exercise on the topics illustrated in the classroom. Students could ask the teacher to solve an exercise in front of the other students about the topics studied during the course. The interested students are kindly asked to contact the main instructor of the course.
The score (up to 2 points) will be added to the score of the written test.

The procedure is as follows:

- Reservation by students is done by sending an e-mail to the teacher. The deadline expires on 9 October 2017.
- The student is given an exercise by the teacher. Presentation of the solution will start from the beginning of November 2017.
- The presentation of the solution is delivered in the classroom using power point.


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


Graduation

List of theses and work experience proposals

theses proposals Research area
Il futuro del corporate reporting (COVID19) Various topics
Le nuove sfide per le supply chain (COVID19) Various topics
Le scelte alimentari dei giovani italiani: quanto è importante la sostenibilità? Various topics
Nuovi scenari e nuovi contesti di acquisto e consumo di bevande alcoliche Various topics
Sfide e opportunità del contesto digitale Various topics
Tesi di Laurea in Economia Comportamentale Various topics

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.