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..

Academic year:
Definition of lesson periods
Period From To
1st semester Oct 1, 2009 Dec 19, 2009
2nd semester Feb 22, 2010 May 22, 2010
Corsi intensivi estivi (sede di Canazei) Jul 11, 2010 Aug 7, 2010
Exam sessions
Session From To
Sessione invernale Jan 7, 2010 Feb 20, 2010
Sessione estiva May 24, 2010 Jul 10, 2010
Sessione autunnale Sep 1, 2010 Sep 30, 2010
Sessione straordinaria Dec 1, 2010 Dec 20, 2010
Holidays
Period From To
Immacolata concezione Dec 8, 2009 Dec 8, 2009
Vacanze Natalizie Dec 21, 2009 Jan 6, 2010
Vacanze Pasquali Apr 2, 2010 Apr 6, 2010
Festa dei Lavoratori May 1, 2010 May 1, 2010
Santo Patrono May 21, 2010 May 21, 2010
Festa dellla Repubblica Jun 2, 2010 Jun 2, 2010
Vacanze estive Aug 9, 2010 Aug 15, 2010

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 M O P R S T

Bombieri Nicola

nicola.bombieri@univr.it +39 045 802 7094

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)

Carlotto Ilaria

ilaria.carlotto@univr.it 045 802 8264

Chesini Giuseppina

giusy.chesini@univr.it 045 802 8495 (VR) -- 0444/393938 (VI)

Corsi Corrado

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

De Sinopoli Francesco

francesco.desinopoli@univr.it 045 842 5450

Duret Paolo

paolo.duret@univr.it 0458028873

Farinon Paolo

paolo.farinon@univr.it 045 802 8169 (VR) 0444/393939 (VI)

Fiorentini Riccardo

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

Lassini Ugo

ugo.lassini@univr.it

Lionzo Andrea

andrea.lionzo@univr.it

Minozzo Marco

marco.minozzo@univr.it 045 802 8234

Omodei Sale' Riccardo

riccardo.omodeisale@univr.it 045 802 8855

Peretti Alberto

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

Pertile Paolo

paolo.pertile@univr.it 045 802 8438

Sommacal Alessandro

alessandro.sommacal@univr.it 045 802 8716

Tondini Giovanni

giovanni.tondini@univr.it Verona: 045 8425449, Vicenza: 0444 393930

Trabucchi Giuseppe

giuseppe.trabucchi@univr.it

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.

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

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-S/01 - STATISTICS

The teaching is organized as follows:

lezione

Credits

7

Period

First semester

Academic staff

Marco Minozzo

esercitazione

Credits

2

Period

First semester

Academic staff

Annamaria Guolo

Learning outcomes

The course provides to students in economic and business sciences an introduction to probability and to descriptive and inferential statistics.
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.

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; fixed and varying base indices; Laspayres and Paasche indices; variability and measures of dispersion; variance and standard deviation; coefficient of variation; moments; Pearson’s and Fisher’s 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; measures of association; chi-squared index of dependence; index of association C; Simpson’s paradox.

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; Poisson distribution; geometric 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; sum of normal 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.

Bibliography

Reference texts
Activity Author Title Publishing house Year ISBN Notes
lezione M. R. Middleton Analisi statistica con Excel Apogeo, Milano 2004
lezione F. P. Borazzo, P. Perchinunno Analisi statistiche con Excel Pearson, Education 2007
lezione S. Bernstein, R. Bernstein Calcolo delle Probabilita', Collana Schaum's, numero 110. McGraw-Hill, Milano 2003
lezione D. OLIVIERI Fondamenti di statistica (Edizione 3) Cedam, Padova 2007
lezione D. OLIVIERI Istituzioni di statistica CEDAM 2005
lezione E. Battistini Probabilità e statistica: un approccio interattivo con Excel McGraw-Hill, Milano 2004
lezione D. Piccolo Statistica Il Mulino 2000 8815075968
lezione S. Bernstein, R. Bernstein Statistica descrittiva, Collana Schaum's, numero 109 McGraw-Hill, Milano 2003
lezione S. Bernstein, R. Bernstein Statistica inferenziale, Collana Schaum's, numero 111. McGraw-Hill, Milano 2003
lezione D. Piccolo Statistica per le decisioni Il Mulino 2004 8815097708
lezione G. Cicchitelli Statistica: principi e metodi (Edizione 2) Pearson Italia, Milano 2012
lezione D. OLIVIERI Temi svolti di statistica (2001-2007) Cedam, Padova 2008

Examination Methods

For the official examination both written and oral sessions are mandatory.
The course is considered completed if the candidate has done the written tests and passed the oral exam.
Students that has received at least 15 out of 30 in both the written exams are allowed to attend the oral exam.

Teaching materials

Type D and Type F activities

Academic year:

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.

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.


Graduation


Student mentoring


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Gestione carriere


Internships


Area riservata studenti