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.
Course calendar
The Academic Calendar sets out the degree programme lecture and exam timetables, as well as the relevant university closure dates..
Period | From | To |
---|---|---|
primo semestre magistrali | Sep 30, 2019 | Dec 20, 2019 |
secondo semestre magistrali | Feb 24, 2020 | May 29, 2020 |
Session | From | To |
---|---|---|
Sessione invernale magistrali | Jan 7, 2020 | Feb 21, 2020 |
Sessione estiva magistrali | Jun 3, 2020 | Jul 10, 2020 |
Autumn Session exams | Aug 24, 2020 | Sep 11, 2020 |
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.
Should you have any doubts or questions, please check the Enrollment FAQs
Academic staff
Bullini Orlandi Ludovico
ludovico.bulliniorlandi@univr.it 045 802 8095Study 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
Modules | Credits | TAF | SSD |
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2° Year activated in the A.Y. 2020/2021
Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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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.
Type D and Type F activities
years | Modules | TAF | Teacher | |
---|---|---|---|---|
1° | Parlare in pubblico e economic writing | D |
Martina Menon
(Coordinator)
|
|
1° | Simulation and Implementation of Economic Policies | D |
Federico Perali
(Coordinator)
|
|
1° 2° | Enactus Verona 2020 | D |
Paola Signori
(Coordinator)
|
|
1° 2° | Samsung Innovation Camp | D |
Marco Minozzo
(Coordinator)
|
years | Modules | TAF | Teacher | |
---|---|---|---|---|
1° | Parlare in pubblico e economic writing | D |
Martina Menon
(Coordinator)
|
|
1° | Simulation and Implementation of Economic Policies | D |
Federico Perali
(Coordinator)
|
|
1° 2° | Predictive analytics for business decisions - 2019/20 | D |
Claudio Zoli
(Coordinator)
|
|
1° 2° | Professional communication for economics - 2019/20 | D |
Claudio Zoli
(Coordinator)
|
|
1° 2° | Regulation, procurement and competition - 2019/20 | D |
Claudio Zoli
(Coordinator)
|
Statistics for Business (2019/2020)
Teaching code
4S008094
Teacher
Coordinator
Credits
6
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-S/03 - ECONOMIC STATISTICS
Period
primo semestre magistrali dal Sep 30, 2019 al Dec 20, 2019.
Learning outcomes
The course aims to provide the basic knowledge for the collection, management and analysis of data of interest in the managerial field. Students' previous statistical knowledge will be integrated with the main statistical sampling techniques for data collection, some of the most widespread techniques for the analysis of time series data, the multiple linear regression, and the most recent techniques for data science in the business context. All these techniques will be discussed in specific areas of application: market research, customer analysis, management control, production process control, sales analysis and forecasting. Special attention will be devoted to some of the most widespread software for data science and business intelligence. At the end of the course, students should demonstrate a good level of understanding both theoretically and practically of the main statistical methods for the analysis of business phenomena, in the light of the available data and the managerial needs. They should also be able to interpret critically the gathered information and the results obtained from the analyses with the aim to supply useful suggestions in support of business decisions.
Program
1) Data sources:
Primary and secondary data.
Internal and external data sources.
2) Probabilistic and non-probabilistic sampling for sample survey:
Review of estimation theory.
Probabilistic sampling design.
Probabilistic sampling for variables.
Determination of the sampling size.
3) Customer analysis:
Pareto chart.
Concentration analysis. The Gini coefficient.
4) Statistical Analysis of sales data. Time Series analysis:
Time series decomposition in trend, seasonality and error.
Moving averages method.
5) Introduction to statistical quality control:
Statistical process control.
Control charts for variables.
The course is taught by lectures.
Lecture slides and other learning materials are available on the e-learning website.
Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|
M. R. Middleton | Analisi statistica con Excel | Apogeo, Milano | 2004 | ||
D. Clark | Beginning Power BI: A Practical Guide to Self-Service Data Analytics with Excel 2016 and Power BI Desktop (Edizione 2) | Apress | 2017 | 9781484225769 | |
R. Sleeper | Practical Tableau: 100 Tips, Tutorials, and Strategies from a Tableau Zen Master | O'Reilly Media, Inc. | 2018 | 9781491977316 | |
B. Bracalente, M. Cossignani, A. Mulas | Statistica Aziendale | McGraw-Hill | 2009 | ||
Luigi Biggeri, Matilde Bini, Alessandra Coli, Laura Grassini, Mauro Maltagliati | Statistica per le decisioni aziendali (Edizione 2) | Pearson Italia | 2017 |
Examination Methods
The assessment of learning outcomes consists in a written examination.
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 soon also via the Univr app.