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..

Definition of lesson periods
Period From To
primo semestre (lauree) Sep 20, 2021 Jan 14, 2022
secondo semestre (lauree) Feb 21, 2022 Jun 1, 2022
Exam sessions
Session From To
sessione invernale Jan 17, 2022 Feb 18, 2022
sessione estiva Jun 6, 2022 Jul 15, 2022
sessione autunnale Aug 22, 2022 Sep 16, 2022
Degree sessions
Session From To
sessione autunnale (validità a.a. 2020/2021) Dec 6, 2021 Dec 10, 2021
sessione invernale (validità a.a. 2020/2021) Apr 6, 2022 Apr 8, 2022
sessione estiva (validità a.a. 2021/2022) Sep 5, 2022 Sep 6, 2022

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 P Q R S Z

Bertoli Paola

paola.bertoli@univr.it 045 8028 508

Brunetti Federico

federico.brunetti@univr.it 045 802 8494

Cantele Silvia

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

Carlotto Ilaria

ilaria.carlotto@univr.it 045 802 8264

Danieli Diletta

diletta.danieli@univr.it

De Crescenzo Veronica

veronica.decrescenzo@univr.it 045 802 8163

Demo Edoardo

edoardo.demo@univr.it 045 802 8782 (VR) 0444.393930 (VI)

Di Caterina Claudia

claudia.dicaterina@univr.it 0458028247

Fiorentini Riccardo

riccardo.fiorentini@univr.it 0444 393934 (VI) - 045 802 8335(VR)

Florio Cristina

cristina.florio@univr.it 045 802 8296

Fratea Caterina

caterina.fratea@univr.it 045 802 8858

Giacomello Bruno

bruno.giacomello@univr.it 0444 393933 (VI)

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Mion Giorgio

giorgio.mion@univr.it 045.802 8172

Peretti Alberto

alberto.peretti@univr.it 0444 393936 (VI) 045 802 8238 (VR)

Pertile Paolo

paolo.pertile@univr.it 045 802 8438

Pilati Andrea

andrea.pilati@univr.it 045 802 8444 (VR) - 0444 393938 (VI)

Quercia Simone

simone.quercia@univr.it 045 802 8237

Ricciuti Roberto

roberto.ricciuti@univr.it 0458028417

Rossi Francesca

francesca.rossi_02@univr.it 045 802 8098

Rossignoli Francesca

francesca.rossignoli@univr.it 0444 393941 (Ufficio Vicenza) 0458028261 (Ufficio Verona)

Scola Sara

sara.scola@univr.it (+39) 045 8028860

Sommacal Alessandro

alessandro.sommacal@univr.it 045 802 8716

Zago Angelo

angelo.zago@univr.it 045 802 8414

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
SECS-P/01
9
A
SECS-S/06
9
C
SECS-P/12
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

4S008933

Credits

9

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-S/03 - ECONOMIC STATISTICS

Period

Primo semestre (lauree) dal Sep 19, 2022 al Jan 13, 2023.

Learning objectives

This module aims at providing students with the main techniques of descriptive statistics, probability theory and statistical inference. In general, these techniques offer a solid ground to perform quantitative analysis of those collective phenomena that are of main interest in business and social sciences. More specifically, methodologies presented in this module are required to describe, interpret and manipulate official data, as well as to carry out an independent statistical analysis in socio-economic contexts. Also, they form the basis of decision analysis in business realities that are becoming increasingly more international. Also, this module aims at offering students the instruments to critically evaluate the proposed techiques.

Prerequisites and basic notions

Basic notions of mathematics (including limits, derivatives, integrals).

Program

1) Descriptive statistics
• Introductory concepts, population and sample, qualitative and quantitative characters
• Types of statistical data, statistical distributions (simple, double, unitary, frequency), graphical representations, histogram
• Cumulative frequencies, step or continuous distribution function
• Location indexes: arithmetic mean, harmonic mean, geometric mean, median, quartiles, deciles, percentiles and quantiles, mode
• Variability indexes: range, interquartile range, simple mean deviations, standard deviation and variance; variance of a linear transformation, standardization; relative indexes of variability: the coefficient of variation
• Indexes of asymmetry and kurtosis
• Double, unitary and frequency distributions; arithmetic mean of the sum of several variables and of the product of two variables; covariance and variance of the sum of several variables; conditional distributions; independence and chi-square dependence index
• Statistical interpolation: least squares method and least squares line, linear correlation coefficient and coefficient of determination R^2; total, explained and residual deviance

2) Probability
• Random experiments, sample space, tree diagrams, random events and operations between events, elements of combinatorial calculus
• Algebras and sigma-algebras, probability spaces, axiomatic definition of probability and its interpretations
• Conditional probability, product law, stochastic independence between events, total probability formula and Bayes' theorem
• Discrete and continuous random variables, distribution function, transformations of random variables, expected value and variance
• Notable discrete distributions: uniform, Bernoulli, binomial
• Notable continuous distributions: uniform and normal
• Discrete double random variables: joint probability distribution, marginal and conditional probability distributions, independence between random variables, covariance, Bravais correlation coefficient
• Linear combinations of random variables, sample mean of independent random variables, sum of independent normal random variables
• (Weak) law of large numbers, Bernoulli's law of large numbers for relative frequencies, central limit theorem

3) Inferential statistics
• Probabilistic samples, sample mean, sample relative frequency, sample variance, chi-squared sample distributions, Student's t
• Point estimate, correctness, efficiency and consistency of the estimators; estimation of mean, proportion, variance
• Interval estimate (confidence interval) for mean, proportion (large samples), variance
• Hypothesis tests: observed power and significance level, one-tailed and two-tailed tests for the mean, for the proportion (large samples) and for the variance; comparison between two means

Bibliography

Visualizza la bibliografia con Leganto, strumento che il Sistema Bibliotecario mette a disposizione per recuperare i testi in programma d'esame in modo semplice e innovativo.

Didactic methods

The course includes 84 hours of lessons, including lectures and exercise sessions. All lectures and exercise sessions are essential for an adequate understanding of the topics covered, as well as individual study. During the course, for each specific topic, the parts of the textbook to be studied are indicated. In addition to the scheduled course hours, several hours of tutoring are also provided as further training support.
All lectures and exercise sessions are held in person. It is advisable to attend the lessons and exercise sessions, taking notes regularly. All the teaching material related to the course (lecture notes, exercises, past exam assignments etc.) is published on the University's E-learning platform (Moodle).

Learning assessment procedures

The final exam is written and consists of three exercises with open questions, both theoretical and practical, on the topics covered in the course. It is allowed to consult a formulary written on a double-sided A4 sheet and the statistical tables, as well as the use of a scientific calculator.

An midterm test is scheduled in November, on about half of the course program. The result, if passed, is added to that of the second partial test taking place with the first exam of the winter session. In each partial test, the exam may include multiple choice questions and the formulary must be prepared on only one A4 side.

Evaluation criteria

Rather than assessing the correctness of the individual numerical results, in the correction of the test primary importance is given to their statistical interpretation within the problem and to the solution of the proposed exercises. Justifying every answer and commenting on the adopted procedures is therefore strongly recommended.

Criteria for the composition of the final grade

The final mark coincides with the score in the final exam, or with the sum of the two partial scores (if both are above a minimum threshold).

Exam language

Italiano

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.

COMPETENZE TRASVERSALI
Scopri i percorsi formativi promossi dal  Teaching and learning centre dell'Ateneo, destinati agli studenti iscritti ai corsi di laurea, volti alla promozione delle competenze trasversali: https://talc.univr.it/it/competenze-trasversali


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.

primo semestre (lauree) From 9/20/21 To 1/14/22
years Modules TAF Teacher
1° 2° Job Club D Paola Signori (Coordinatore)
1° 2° Marketing plan D Virginia Vannucci (Coordinatore)
1° 2° Soft skills Coaching Days (Esu 4 job) - 2021/2022 D Paola Signori (Coordinatore)
Periodo generico From 10/1/21 To 5/31/22
years Modules TAF Teacher
1° 2° Internationalization and Sustainability. Friends or Enemies? D Angelo Zago (Coordinatore)
1° 2° Internationalization and Sustainability. Friends or Enemies? D Angelo Zago (Coordinatore)
1° 2° Internationalization and Sustainability. Friends or Enemies? D Angelo Zago (Coordinatore)
1° 2° Data Visualization Laboratory D Marco Minozzo (Coordinatore)
1° 2° Python Laboratory D Marco Minozzo (Coordinatore)
1° 2° Data Science Laboratory with SAP D Marco Minozzo (Coordinatore)
1° 2° Programming in Matlab D Marco Minozzo (Coordinatore)
1° 2° Programming in SAS D Marco Minozzo (Coordinatore)
1° 2° Samsung Innovation Camp D Marco Minozzo (Coordinatore)
primo semestre (lauree magistrali) From 10/4/21 To 12/17/21
years Modules TAF Teacher
1° 2° What paradigms beyond the pandemic? Individual vs. Society, Private vs. Public D Federico Brunetti (Coordinatore)
secondo semestre (lauree) From 2/21/22 To 6/1/22
years Modules TAF Teacher
1° 2° AN INTRODUCTION TO LATEX TYPESETTING SYSTEM D Alberto Peretti (Coordinatore)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° Data Analysis Laboratory with R (Vicenza) D Marco Minozzo (Coordinatore)
1° 2° Advanced Excel Laboratory (Vicenza) D Marco Minozzo (Coordinatore)
1° 2° Excel Laboratory (Vicenza) D Marco Minozzo (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.

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