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.

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.

Academic year:
Second semester bachelor degree From 2/17/20 To 6/5/20
years Modules TAF Teacher
1° 2° 3° Soft skills coaching days Vicenza D Paola Signori (Coordinator)
(Verona) Second semester bachelor degree From 2/17/20 To 6/5/20
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)
Second semester bachelor degree From 2/24/20 To 5/29/20
years Modules TAF Teacher
1° 2° 3° Simulation and Implementation of Economic Policies D Federico Perali (Coordinator)
(Verona) secondo semestre magistrali From 2/24/20 To 5/29/20
years Modules TAF Teacher
1° 2° 3° Parlare in pubblico e economic writing D Martina Menon (Coordinator)
List of courses with unassigned period
years Modules TAF Teacher
1° 2° 3° Il Futuro Conta! D Alessandro Bucciol (Coordinator)
1° 2° 3° Il Futuro Conta! D Alessandro Bucciol (Coordinator)
1° 2° 3° Data Analysis Laboratory with R D Marco Minozzo (Coordinator)
1° 2° 3° Data Analysis Laboratory with R (Vicenza) D Marco Minozzo (Coordinator)
1° 2° 3° Data Visualization Laboratory D Marco Minozzo (Coordinator)
1° 2° 3° Python Laboratory D Marco Minozzo (Coordinator)
1° 2° 3° Data Science Laboratory with SAP D Marco Minozzo (Coordinator)
1° 2° 3° Advanced Excel Laboratory (Vicenza) D Marco Minozzo (Coordinator)
1° 2° 3° Excel Laboratory (Vicenza) D Marco Minozzo (Coordinator)
1° 2° 3° The fashion lab (1 ECTS) D Angela Broglia (Coordinator)
1° 2° 3° The fashion lab (2 ECTS) D Angela Broglia (Coordinator)
1° 2° 3° The fashion lab (3 ECTS) D Angela Broglia (Coordinator)
1° 2° 3° Marketing Plan D Ilenia Confente (Coordinator)
1° 2° 3° Presente e futuro del pianeta D Federico Brunetti (Coordinator)
1° 2° 3° Programming in Matlab D Marco Minozzo (Coordinator)
1° 2° 3° Programming in SAS D Marco Minozzo (Coordinator)
1° 2° 3° Robo-Ethics D Giorgio Mion (Coordinator)
1° 2° 3° Univero' - Job Orienteering festival D Paola Signori (Coordinator)

Teaching code

4S00121

Academic staff

Coordinator

Credits

9

Also offered in courses:

  • Statistics of the course Bachelor's degree in Business Administration (Vicenza)

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-S/01 - STATISTICS

Period

primo semestre lauree triennali dal Sep 17, 2018 al Jan 11, 2019.

Learning outcomes

This module provides 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 undergraduate calculus. In general, this module aims to offers a toolkit to investigate collective phenomena, starting from conducting a simple descriptive analysis to performing more formal hypothesis testing. The theoretical techniques students will acquire by the end of the course are necessary for descriptive, interpretative and decision-making purposes, as well as, more generally, for carrying out statistical studies related to economic and social phenomena. In addition to offering the necessary mathematical apparatus, the course also aims at providing the conceptual tools for a critical evaluation of the methodologies considered.

Program

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; method of least squares; least-squares regression line; Pearson’s coefficient of linear correlation r; Cauchy-Schwarz inequality; R-square coefficiente; deviance residual and deviance explained; multivariate frequency distributions; conditional distributions; chi-squared index of dependence; index of association C.

Probability: events, probability spaces and event trees; combinatorics; conditional probability; independence; Bayes theorem; discrete and continuous random variables; distribution function; expectation and variance; Markov and Tchebycheff inequalities; discrete uniform distribution; Bernoulli distribution; binomial distribution; continuous uniform distribution; 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 random variables; weak law of large numbers; Bernoulli’s law of large numbers for relative frequencies; central limit theorem.

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; 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.

The course consists of a series of lectures (56 hours) and of twelve exercise classes (24 hours).
All classes are essential to a proper understanding of the topics of the course.
The working language is Italian.

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 final exam consists of a two-hours written exam paper containing both practical exercises and theoretical definitions and derivations. Students are allowed to use a calculator, but no other material (such as books, notes, etc.). There is no compulsory oral examination, but students who get a mark of at least 15/18 have the option of integrating their mark by means of an interview. The oral examination offers the possibility of gaining or losing up to three marks compared to the result of their script. Students are expected to show an id (or student's card) in order to sit the exam.

An intermediate examination paper on the first part of the program is planned and students can take it on a voluntary basis. Students who successfully pass the intermediate examination have the option of taking a similar paper on the second part of the module during the exam session immediately after the end of the course, rather than sitting the full final exam paper. The two partial examination will have the same weight on the final mark, and each of them has to be passed with a mark of at least 8/30. Accurate notification about the topics covered in the first partial examination will be posted on the course webpage in due course. Students are encouraged to take the intermediate examination, not only in view of splitting the examinable material in two parts, but also and especially to self-assess progresses and weaknesses in a timely and efficient manner.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE