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 |
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First semester | Oct 4, 2010 | Dec 22, 2010 |
Second semester | Feb 21, 2011 | May 25, 2011 |
Session | From | To |
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Winter session | Jan 10, 2011 | Feb 19, 2011 |
Summer session | May 30, 2011 | Jul 9, 2011 |
Autumn session | Aug 29, 2011 | Sep 24, 2011 |
Period | From | To |
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All Saints | Nov 1, 2010 | Nov 1, 2010 |
National holiday | Dec 8, 2010 | Dec 8, 2010 |
Christmas holidays | Dec 22, 2010 | Jan 6, 2011 |
Easter holidays | Apr 22, 2011 | Apr 26, 2011 |
National holiday | Apr 25, 2011 | Apr 25, 2011 |
Labour Day | May 1, 2011 | May 1, 2011 |
National holiday | Jun 2, 2011 | Jun 2, 2011 |
Summer holidays | Aug 8, 2011 | Aug 15, 2011 |
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
Lassini Ugo
ugo.lassini@univr.itLionzo Andrea
andrea.lionzo@univr.itNovello Diego
avv.novello@studionovelloepartners.itStudy 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. 2011/2012
Modules | Credits | TAF | SSD |
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3° Year activated in the A.Y. 2012/2013
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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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 (2011/2012)
Teaching code
4S00121
Credits
9
Language
Italian
Also offered in courses:
- Statistics of the course Bachelor's degree in Economics and Business (Vicenza)
- Statistics of the course Bachelor's degree in Economics and Business (Vicenza)
- Statistics of the course Bachelor's degree in Economics and Business (Vicenza)
Scientific Disciplinary Sector (SSD)
SECS-S/01 - STATISTICS
The teaching is organized as follows:
lezione
esercitazione
Learning outcomes
The course is intended to provide an introduction to Descriptive Statistics, Probability and Inferential Statistics. The course is for 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 first year introductory course in calculus. The statistical techniques that will be illustrate 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 realizing 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 more variables; conditional distributions; conditional mean and variance;
scatterplots; covariance; variance of the sum of more variables; chi-squared index of dependence; index of association C.
Least squares metodo; scatterplot; least-squares regression line; Pearson’s coefficient of linear correlation r; Cauchy-Schwarz inequality; R-square coefficiente; 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 (2008), Statistica: principi e metodi, Pearson Education, Milano.
Additional material will be distributed by the teacher
Other books
- D. PICCOLO (1998), Statistica, Seconda edizione 2000. Il Mulino, Bologna.
- D. PICCOLO (2010), Statistica per le decisioni, Nuova edizione. Il Mulino, Bologna.
- D. OLIVIERI (2003), Temi svolti di statistica, Seconda edizione aggiornata al 2002. Cedam, Padova.
- D. OLIVIERI (2005), Istituzioni di statistica. Cedam, Padova.
– D. OLIVIERI (2007), Fondamenti di statistica, Terza edizione. Cedam, Padova.
- E. BATTISTINI (2004), Probabilità e statistica: un approccio interattivo con Excel. McGraw-Hill, Milano.
- S. BERNSTEIN, R. BERNSTEIN (2003), Statistica descrittiva, Collana Schaum's, numero 109. McGraw-Hill, Milano.
- S. BERNSTEIN, R. BERNSTEIN (2003), Calcolo delle probabilita', Collana Schaum's, numero 110. McGraw-Hill, Milano.
- S. BERNSTEIN, R. BERNSTEIN (2003), Statistica inferenziale, Collana Schaum's, numero 111. McGraw-Hill, Milano.
- F. P. BORAZZO, P. PERCHINUNNO (2007), Analisi statistiche con Excel. Pearson, Education.
- M. R. MIDDLETON (2004), Analisi statistica con Excel. Apogeo.
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.
The exercise lessons are necessary to better understand the course. The material which will be used during the exercise lessons will be made available online.
Bibliography
Activity | Author | Title | Publishing house | Year | ISBN | Notes |
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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 | Libro di testo | |
lezione | D. OLIVIERI | Temi svolti di statistica (2001-2007) | Cedam, Padova | 2008 |
Examination Methods
The course is considered completed if the candidate has passed both the two written tests. Students must receive at least 15 out of 30 in both written tests.
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: only in this way will you be able to receive notification of all the notices from your teachers and your secretariat via email and also via the Univr app.
Graduation
Student mentoring
Linguistic training CLA
Gestione carriere
Internships
The curriculum of the three-year degree courses (CdL) and master's degree courses (CdLM) in the economics area includes an internship as a compulsory training activity. Indeed, the internship is considered an appropriate tool for acquiring professional skills and abilities and for facilitating the choice of a future professional outlet that aligns with one's expectations, aptitudes, and aspirations. The student can acquire further competencies and interpersonal skills through practical experience in a work environment.