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 |
---|---|---|
First semester bachelor degree | Sep 16, 2019 | Jan 10, 2020 |
Second semester bachelor degree | Feb 17, 2020 | Jun 5, 2020 |
Session | From | To |
---|---|---|
First semester intermediate tests | Nov 4, 2019 | Nov 8, 2019 |
Winter exam session | Jan 13, 2020 | Feb 14, 2020 |
Second semester intermediate tests | Apr 15, 2020 | Apr 17, 2020 |
Summer session exam | Jun 8, 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.
Academic staff
![Elena Manzoni, February 4, 2020](https://docs.univr.it/documenti//Persona/foto/foto720236.jpg)
Manzoni Elena
![profilo, January 21, 2019](https://docs.univr.it/documenti//Persona/foto/foto829865.jpg)
Santi Flavio
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
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2° Year activated in the A.Y. 2020/2021
Modules | Credits | TAF | SSD |
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3° Year activated in the A.Y. 2021/2022
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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.
Statistics (2020/2021)
Teaching code
4S00121
Academic staff
Coordinator
Credits
9
Language
Italian
Scientific Disciplinary Sector (SSD)
SECS-S/01 - STATISTICS
Period
primo semestre (lauree) dal Sep 28, 2020 al Dec 23, 2020.
Learning outcomes
The course aims at providing the basic techniques of descriptive statistics, probability and statistical inference to undergraduate students in economic and business sciences. Prerequisite to the course is the mastering of a few basic mathematical concepts such as limit, derivative and integration at the level of an undergraduate introductory course in calculus. Overall, these techniques provide the necessary toolkit for quantitative analysis in processes related to the observation and understanding of collective phenomena. From a practical point of view, they are necessary for descriptive, interpretative and decision-making purposes when carrying out statistical studies related to economic and social phenomena. In addition to providing the necessary mathematical apparatus, the course aims at providing conceptual tools for a 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.
• Fixed-base indices and chain indices; Laspayres and Paasche indices.
• 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; index of association C; Simpson’s paradox.
• Method of least squares; least-squares regression line; Pearson’s coefficient of linear correlation r; Cauchy-Schwarz inequality; R-square coefficient; explained deviance and residual deviance.
b) Probability
• Random events; algebras and sigma-algebras; probability spaces and event trees; combinatorics.
• Conditional probability; independence; Bayes theorem.
• Discrete and continuous random variables; distribution function; expectation and variance; Markov and Chebyshev inequalities.
• Discrete uniform distributions; Bernoulli distribution; binomial distribution; Poisson distribution; geometric distribution.
• Continuous uniform distributions; normal distribution; exponential distribution.
• 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 and 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-t distribution; Snedecors-F distribution.
• Point estimates and estimators; unbiasedness; efficiency; consistency; estimate of the mean, of a proportion and of a variance.
• Confidence intervals for a mean, for a proportion (large samples) and for a variance.
• Hypothesis testing; power and observed significance level; one and two tails tests for a mean, for a proportion (large samples) and for a variance; hypothesis testing for differences in two means, two proportions (large samples) and two variances.
SUPPORTING MATERIAL
Detailed indications, regarding the use of the textbook, will be given during the course. Supporting material (written records of the lessons, exercises with solutions, past exam papers with solutions, etc.) is available on the E-learning platform of the University (Moodle).
TEACHING METHODS
Students are supposed to have acquired mathematical knowledge of basic concepts such as limit, derivative and integral.
Course load is equal to 84 hours. Exercise sessions are an integral part of the course and, together with the classes, they are essential to a proper understanding of the topics of the course. The working language is Italian. In addition to lessons and exercise hours, there will also be tutoring hours devoted to revision. More detailed information will be available during the course.
Due to the COVID-19 health emergency, the way lessons will be delivered might change during the course of the semester. In any case, distance learning will always be guaranteed so that all face-to-face lessons, in addition to telematic ones (pre-recorded or online), will be recorded and made available for later viewing.
Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|
D. Giuliani, M. M. Dickson | Analisi statistica con Excel | Maggioli Editore | 2015 | 8838789908 | Reading list |
M. R. Middleton | Analisi statistica con Excel | Apogeo, Milano | 2004 | Reading list | |
F. P. Borazzo, P. Perchinunno | Analisi statistiche con Excel | Pearson, Education | 2007 | Reading list | |
S. Bernstein, R. Bernstein | Calcolo delle Probabilita', Collana Schaum's, numero 110. | McGraw-Hill, Milano | 2003 | Reading list | |
A. Azzalini | Inferenza Statistica: Una presentazione basata sul concetto di verosimiglianza (Edizione 2) | Springer Verlag Italia | 2001 | 9788847001305 | Laurea in Matematica Applicata |
E. Battistini | Probabilità e statistica: un approccio interattivo con Excel | McGraw-Hill, Milano | 2004 | Reading list | |
D. Piccolo | Statistica | Il Mulino | 2000 | 8815075968 | Reading list |
S. Bernstein, R. Bernstein | Statistica descrittiva, Collana Schaum's, numero 109 | McGraw-Hill, Milano | 2003 | Reading list | |
S. Bernstein, R. Bernstein | Statistica inferenziale, Collana Schaum's, numero 111. | McGraw-Hill, Milano | 2003 | Reading list | |
D. Piccolo | Statistica per le decisioni | Il Mulino | 2004 | 8815097708 | Reading list |
P. Klibanoff, A. Sandroni, B. Moselle, B. Saraniti | Statistica per manager (Edizione 1) | Egea | 2010 | 9788823821347 | Reading list |
G. Cicchitelli, P. D'Urso, M. Minozzo | Statistica: principi e metodi (Edizione 3) | Pearson Italia, Milano | 2018 | 9788891902788 | Textbook |
D. M. Levine, D. F. Stephan, K. A. Szabat | Statistics for Managers Using Microsoft Excel, Global Edition (Edizione 7) | Pearson | 2014 | 0133061817 | Reading list |
Examination Methods
Due to the COVID-19 health emergency, at the moment it is not possible to predict whether the final examination will be face-to-face or remotely. If the examination will be held face-to-face, it will consist of a written test (lasting about 2 hours and 30 minutes) made up of a selection of exercises and multiple choice questions. For the written test, only a calculator can be used and no other material (books, notes, etc.) will be allowed. The written test will be followed by an oral test (optional), which can only be accessed by students who have obtained a mark greater than or equal to 15/30 both in the exercises and in the multiple choice questions. To take the tests, students must present themselves with a university card or a suitable identification document.
In the event that the examination will be held remotely, it will consist of a written test through Moodle's QUIZ tool (lasting about 1 hour and 15 minutes) made up of a selection of numerical exercises and multiple choice questions. The written test will be followed by a compulsory oral test, which can only be accessed by students who have obtained a sufficiently adequate mark in the written test. The oral exam will also take place remotely through Zoom.
For the 2020/2021 academic year, remote examination is always guaranteed for all students who request it. Regardless of the modality (face-to-face or remotely), the exams will be calibrated to guarantee the same level of difficulty. Finally, we remind that the examination methods are the same for all students and there are no differences according to the number of lessons attended.
Type D and Type F activities
Nei piani didattici di ciascun Corso di studio è previsto l’obbligo di conseguire un certo numero di crediti formativi mediante attività a scelta (chiamate anche "di tipologia D e F").
Oltre che in insegnamenti previsti nei piani didattici di altri corsi di studio e in certificazioni linguistiche o informatiche secondo quanto specificato nei regolamenti di ciascun corso, tali attività possono consistere anche in iniziative extracurriculari di contenuto vario, quali ad esempio la partecipazione a un seminario o a un ciclo di seminari, la frequenza di laboratori didattici, lo svolgimento di project work, stage aggiuntivo, eccetera.
Come per ogni altra attività a scelta, è necessario che anche queste non costituiscano un duplicato di conoscenze e competenze già acquisite dallo studente.
Quelle elencate in questa pagina sono le iniziative extracurriculari che sono state approvate dal Consiglio della Scuola di Economia e Management e quindi consentono a chi vi partecipa l'acquisizione dei CFU specificati, alle condizioni riportate nelle pagine di dettaglio di ciascuna iniziativa.
Si ricorda in proposito che:
- tutte queste iniziative richiedono, per l'acquisizione dei relativi CFU, il superamento di una prova di verifica delle competenze acquisite, secondo le indicazioni contenute nella sezione "Modalità d'esame" della singola attività;
- lo studente è tenuto a inserire nel proprio piano degli studi l'attività prescelta e a iscriversi all'appello appositamente creato per la verbalizzazione, la cui data viene stabilita dal docente di riferimento e pubblicata nella sezione "Modalità d'esame" della singola attività.
ATTENZIONE: Per essere ammessi a sostenere una qualsiasi attività didattica, inlcuse quelle a scelta, è necessario essere iscritti all'anno di corso in cui essa viene offerta. Si raccomanda, pertanto, ai laureandi delle sessioni di dicembre e aprile di NON svolgere attività extracurriculari del nuovo anno accademico, cui loro non risultano iscritti, essendo tali sessioni di laurea con validità riferita all'anno accademico precedente. Quindi, per attività svolte in un anno accademico cui non si è iscritti, non si potrà dar luogo a riconoscimento di CFU.
years | Modules | TAF | Teacher |
---|---|---|---|
1° 2° 3° | Enactus Verona 2020 | D |
Paola Signori
(Coordinator)
|
1° 2° 3° | Parlare in pubblico e economic writing | D |
Martina Menon
(Coordinator)
|
1° 2° 3° | Samsung Innovation Camp | D |
Marco Minozzo
(Coordinator)
|
1° 2° 3° | Simulation and Implementation of Economic Policies | D |
Federico Perali
(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 soon also via the Univr app.
Graduation
List of theses and work experience proposals
theses proposals | Research area |
---|---|
Tesi di laurea - Il credit scoring | Statistics - Foundational and philosophical topics |
La performance delle imprese che adottano politiche di Corporate Social responsibility | Various topics |
La previsione della qualita' dei vini: Il caso dell'Amarone | Various topics |
Proposte di tesi | Various topics |
Tesi in Macroeconomia | Various topics |
tesi triennali | Various topics |