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. 2014/2015

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 Sep 15, 2014 Jan 9, 2015
Secondo semestre Feb 19, 2015 May 29, 2015
Exam sessions
Session From To
prove intermedie (primo semestre) Nov 3, 2014 Nov 7, 2014
sessione invernale Jan 12, 2015 Feb 18, 2015
prove intermedie (secondo semestre) Apr 13, 2015 Apr 17, 2015
sessione estiva Jun 4, 2015 Jul 11, 2015
sessione autunnale Aug 24, 2015 Sep 9, 2015
Degree sessions
Session From To
sessione autunnale Dec 12, 2014 Dec 19, 2014
sessione invernale Apr 8, 2015 Apr 10, 2015
sessione estiva Sep 10, 2015 Sep 11, 2015
Holidays
Period From To
festività natalizie Dec 22, 2014 Jan 5, 2015
festività pasquali Apr 3, 2015 Apr 7, 2015
vacanze estive Aug 10, 2015 Aug 22, 2015

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 L O P R S T V

Bonfanti Angelo

angelo.bonfanti@univr.it 045 802 8292

Brunetti Federico

federico.brunetti@univr.it 045 802 8494

Cantele Silvia

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

Corsi Corrado

corrado.corsi@univr.it 045 802 8452 (VR) 0444/393937 (VI)

Cubico Serena

serena.cubico@univr.it 045 802 8132

De Crescenzo Veronica

veronica.decrescenzo@univr.it 045 802 8163

Durastante Paolo

paolo.durastante@univr.it 0444962826

Faccincani Lorenzo

lorenzo.faccincani@univr.it 045 802 8610

Faccioli Mirko

mirko.faccioli@univr.it +39 045 8028879

Fiorentini Riccardo

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

Fioroni Tamara

tamara.fioroni@univr.it 0458028489

Giacomello Bruno

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

Levati Maria Vittoria

vittoria.levati@univr.it 045 802 8640

Lionzo Andrea

andrea.lionzo@univr.it

Ortoleva Maria Grazia

mariagrazia.ortoleva@univr.it 045 802 8052

Peluso Eugenio

eugenio.peluso@univr.it 045 8028104

Peretti Alberto

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

Pertile Paolo

paolo.pertile@univr.it 045 802 8438

Pichler Flavio

flavio.pichler@univr.it 045 802 8273

Rossignoli Francesca

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

Rutigliano Michele

michele.rutigliano@univr.it 0458028610

Signori Paola

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

Sommacal Alessandro

alessandro.sommacal@univr.it 045 802 8716

Tescaro Mauro

mauro.tescaro@univr.it 045 802 8880

Trabucchi Giuseppe

giuseppe.trabucchi@univr.it

Veronesi Marcella

marcella.veronesi@univr.it 045 802 8025

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
(IUS/01)
9
B
(SECS-P/08)
6
C
(IUS/09)
9
A
(SECS-P/01)
9
A
(SECS-S/06)
ModulesCreditsTAFSSD
9
B
(IUS/04)
9
B
(SECS-P/01)
9
B
(SECS-P/07)
9
B
(SECS-P/07)
9
B
(SECS-P/03)
9
B
(SECS-S/01)
ModulesCreditsTAFSSD
9
B
(SECS-P/01)
6
B
(SECS-P/08)
6
C
(SECS-P/10)
6
S
(-)
Prova finale
3
E
(-)

1° Year

ModulesCreditsTAFSSD
9
A
(IUS/01)
9
B
(SECS-P/08)
6
C
(IUS/09)
9
A
(SECS-P/01)
9
A
(SECS-S/06)

2° Year

ModulesCreditsTAFSSD
9
B
(IUS/04)
9
B
(SECS-P/01)
9
B
(SECS-P/07)
9
B
(SECS-P/07)
9
B
(SECS-P/03)
9
B
(SECS-S/01)

3° Year

ModulesCreditsTAFSSD
9
B
(SECS-P/01)
6
B
(SECS-P/08)
6
C
(SECS-P/10)
6
S
(-)
Prova finale
3
E
(-)
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.




SPlacements in companies, public or private institutions and professional associations

Teaching code

4S00121

Credits

9

Scientific Disciplinary Sector (SSD)

SECS-S/01 - STATISTICS

Language

Italian

The teaching is organized as follows:

lezione

Credits

7

Period

Primo semestre

Academic staff

Annamaria Guolo

esercitazione

Credits

2

Period

Primo semestre

Academic staff

Giovanna Caramia

Learning outcomes

The course is intended to provide an introduction to Descriptive Statistics, Probability, and Inferential Statistics. The course is for students in Economics and Business Administration. 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 first year introductory course in calculus. The statistical techniques that will be illustrated in the course are intended to provide instruments useful for description and interpretation of collective data. From a practical point of view, methods are necessary for interpreting official statistics and for performing statistical studies of economical and social phenomena. The course is also intended to provide instruments for a critical analysis of the methodology.

Program

a) Descriptive Statistics

Introduction; data collection; population, sample, statistical unit; survey; questionnaire; data classification; data types; statistical sources.
Statistical data; matrix data; types of frequency distributions; graphical representations.
Cumulative frequency; cumulative distribution function.
Measures of central tendency; arithmetic mean, geometric mean and harmonic mean; properties of the arithmetic mean; quadratic and cubic mean; mood; median; quartiles and percentiles.
Variability and measures of dispersion; variance and standard deviation; coefficient of variation.
Moments; indices of skewness and kurtosis.
Fixed and varying base indices; Laspayres and Paasche indices.
Double and multivariate distributions; frequency tables; covariance; variance of the sum of two or more than two variables; conditional distributions; conditional mean and variance; scatterplots; covariance; variance of the sum of two or more than two variables; chi-squared index of dependence; index of association C.
Least squares metod; scatterplot; least-squares regression line; Pearson’s coefficient of linear correlation r; Cauchy-Schwarz inequality; R-square coefficient; regression and residual deviance.

b) Probability

Deterministic and probabilistic models; events, probability spaces and event trees.
Combinatorics.
Definition and probability; probability function; theorems; 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; Poisson distribution; continuous uniform distribution; normal distribution; multivariate discrete random variables; joint probability distribution; marginal and conditional probability distributions; independence; expectation and covariance; correlation coefficient; conditional expectation and variance.
Linear combinations of random variables; average of random variables; sum of independent normals.
Weak law of large numbers.
Central limit theorem.

c) Inferential Statistics

Introduction; sample and sampling variability; sample statistics and sampling distributions.
Point estimates and estimators; unbiasedness; efficiency; consistency; estimate of the mean, of a proportion, and of a variance.
Confidence intervals; intervals for a mean, for a proportion (large samples) and for a variance.
Hypothesis testing; first- and second-type errors and power of a test; 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.

Book

- G. CICCHITELLI (2012), Statistica: principi e metodi, Second edition, Pearson Italia, Milano.

Other books

- D. PICCOLO (1998), Statistica, Second edition 2000. Il Mulino, Bologna.
- D. PICCOLO (2010), Statistica per le decisioni, New edition. Il Mulino, Bologna.
- M. R. MIDDLETON (2004), Analisi statistica con Excel. Apogeo.
- E. BATTISTINI (2004), Probabilità e statistica: un approccio interattivo con Excel. McGraw-Hill, Milano.
- F. P. BORAZZO, P. PERCHINUNNO (2007), Analisi statistiche con Excel. Pearson, Education.

Details

The course consists of a series of lectures (56 hours) and of twelve exercise classes (24 hours). The working language is Italian.

It is assumed that students have a basic knowledge of mathematics, in particular about limits, derivation methods, and integration techniques.

The material which will be used during the exercise lessons will be made available online (e-learning).

Examination Methods

The examination consists of two separate tests, one with a series of questions, and one with some exercises. The total examination will take about 2 hours and 30 minutes.
The examination is considered successful if the candidate has passed both the two written tests: students must receive at least 16 out of 30 in both written tests, and the final average score has to be at least equal to 18/30. Final scores equal to 16/30 or 17/30 allow students to face an oral and optional examination.
No books or personal material are allowed during the examination. Only the calculating machine is allowed. Material to use for evaluating the quantiles or the probabilities of statistical distributions will be made available by the teacher during the examination. The students are required to attend the examination with the identity card or a similar document.
In mid-November 2014, students have the opportunity to take an intermediate examination on the first part of the program. The intermediate examination (about 1 hour) consists in a series of questions. The final positive score will be considered during the two Winter examination sessions. The final score of the intermediate examination can provide an increase of at most three points of the (positive) result of the written examination of the Winter sessions.

Type D and Type F activities

Modules not yet included

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.

Gestione carriere


Student mentoring


Graduation


Internships


Linguistic training CLA


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.