## 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 |
---|---|---|

primo semestre triennali | Sep 19, 2016 | Jan 13, 2017 |

secondo semestre triennali | Feb 20, 2017 | Jun 1, 2017 |

Session | From | To |
---|---|---|

Prove intermedie primo semestre | Nov 7, 2016 | Nov 11, 2016 |

Appelli esami sessione invernale | Jan 16, 2017 | Feb 17, 2017 |

Prove intermedie secondo semestre | Apr 10, 2017 | Apr 13, 2017 |

Appelli esami sessione estiva | Jun 5, 2017 | Jul 7, 2017 |

Appelli esami sessione autunnale | Aug 28, 2017 | Sep 15, 2017 |

Session | From | To |
---|---|---|

Sessione autunnale | Nov 30, 2016 | Dec 1, 2016 |

Sessione invernale | Apr 5, 2017 | Apr 7, 2017 |

Sessione estiva | Sep 11, 2017 | Sep 13, 2017 |

Period | From | To |
---|---|---|

Vacanze natalizie | Dec 23, 2016 | Jan 5, 2017 |

Vacanze pasquali | Apr 14, 2017 | Apr 18, 2017 |

Vacanze estive | Aug 7, 2017 | Aug 25, 2017 |

## 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

Mussini Mauro

mauro.mussini@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.

Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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Modules | Credits | TAF | SSD |
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1° Year

Modules | Credits | TAF | SSD |
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2° Year activated in the A.Y. 2017/2018

Modules | Credits | TAF | SSD |
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3° Year activated in the A.Y. 2018/2019

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 (2017/2018)

Teaching code

4S00121

Academic staff

Coordinatore

Credits

9

Language

Italian

Scientific Disciplinary Sector (SSD)

SECS-S/01 - STATISTICS

Period

Primo Semestre Triennali dal Sep 18, 2017 al Jan 12, 2018.

## Learning outcomes

The course aims to provide 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 an undergraduate first year introductory course in calculus. Overall, these techniques provide the necessary toolkit for quantitative analysis in the processes related to the observation and understanding of collective phenomena. From a practical point of view, they are necessary for descriptive, interpretative and decision-making purposes and for conducting statistical studies related to economic and social phenomena. In addition to providing the necessary mathematical apparatus, the course also aims at providing the conceptual tools for a critical evaluation of the methodologies considered.

## Program

a) 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-base indices and chain indices; Laspayres and Paasche indices.

• 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.

• Multivariate frequency distributions; conditional distributions; chi-squared index of dependence; index of association C; Simpson’s paradox.

• Method of least squares; least-squares regression line; Pearson’s coefficient of linear correlation r; Cauchy-Schwarz inequality; R-square coefficient; explained deviance and residual deviance.

b) Probability

• Random 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 distributions; Bernoulli distribution; binomial distribution; Poisson distribution; geometric distribution.

• Continuous uniform distributions; 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 independent random variables; sum of independent and Gaussian random variables.

• Weak law of large numbers; Bernoulli’s law of large numbers for relative frequencies; central limit theorem.

c) 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.

Textbook

- G. CICCHITELLI, P. D’URSO, M. MINOZZO (2018), Statistica: principi e metodi, Terza edizione, Pearson Italia, Milano.

Reading list

- A. AZZALINI (2001), Inferenza statistica: una presentazione basata sul concetto di verosimiglianza, Seconda edizione. Springer Verlag Italia.

- 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 probabilità, 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.

- D. GIULIANI, M. M. DICKSON (2015), Analisi statistica con Excel. Maggioli Editore.

- P. KLIBANOFF, A. SANDRONI, B. MODELLE, B. SARANITI (2010), Statistica per manager, Prima edizione, Egea.

- D. M. LEVINE, D. F. STEPHAN, K. A. SZABAT (2014), Statistics for Managers Using Microsoft Excel, Seventh Edition, Global Edition. Pearson.

- M. R. MIDDLETON (2004), Analisi statistica con Excel. Apogeo.

- D. PICCOLO (1998), Statistica, Seconda edizione 2000. Il Mulino, Bologna.

- D. PICCOLO (2010), Statistica per le decisioni, Nuova edizione. Il Mulino, Bologna.

Study guide

Detailed indications, regarding the use of the textbook, will be given during the course. Supporting material (written records of the lessons, exercises with solutions, past exam papers with solutions, etc.) is available on the E-learning platform of the University.

Prerequisites

Students are supposed to have acquired mathematical knowledge of basic concepts such as limit, derivative and integral.

Teaching methods

Course load is equal to 80 hours: 56 lecture hours (equal to 7 ECTS) and 24 exercise hours (equal to 2 ECTS). All classes are essential to a proper understanding of the topics of the course. The working language is Italian.

Exercise sessions

Exercise sessions are integral part of the course and are necessary to an adequate understanding of the topics.

Tutoring activities

In addition to lessons and exercise hours, before each exam session there will be tutoring hours devoted to revision. More detailed information will be available during the course.

Author | Title | Publishing house | Year | ISBN | Notes |
---|---|---|---|---|---|

D. Giuliani, M. M. Dickson | Analisi statistica con Excel | Maggioli Editore | 2015 | 8838789908 | |

M. R. Middleton | Analisi statistica con Excel | Apogeo, Milano | 2004 | ||

F. P. Borazzo, P. Perchinunno | Analisi statistiche con Excel | Pearson, Education | 2007 | ||

S. Bernstein, R. Bernstein | Calcolo delle Probabilita', Collana Schaum's, numero 110. | McGraw-Hill, Milano | 2003 | ||

A. Azzalini | Inferenza Statistica: Una presentazione basata sul concetto di verosimiglianza (Edizione 2) | Springer Verlag Italia | 2001 | 9788847001305 | Laurea in Matematica Applicata |

E. Battistini | Probabilità e statistica: un approccio interattivo con Excel | McGraw-Hill, Milano | 2004 | ||

D. Piccolo | Statistica | Il Mulino | 2000 | 8815075968 | |

S. Bernstein, R. Bernstein | Statistica descrittiva, Collana Schaum's, numero 109 | McGraw-Hill, Milano | 2003 | ||

S. Bernstein, R. Bernstein | Statistica inferenziale, Collana Schaum's, numero 111. | McGraw-Hill, Milano | 2003 | ||

D. Piccolo | Statistica per le decisioni | Il Mulino | 2004 | 8815097708 | |

P. Klibanoff, A. Sandroni, B. Moselle, B. Saraniti | Statistica per manager (Edizione 1) | Egea | 2010 | 9788823821347 | |

G. Cicchitelli, P. D'Urso, M. Minozzo | Statistica: principi e metodi (Edizione 3) | Pearson Italia, Milano | 2018 | 9788891902788 | Libro di testo |

D. M. Levine, D. F. Stephan, K. A. Szabat | Statistics for Managers Using Microsoft Excel, Global Edition (Edizione 7) | Pearson | 2014 | 0133061817 |

## Examination Methods

The final exam consists of a written test (of two hours and 30 minutes) with classical exercises and multiple choice questions. For the written test, students can use a scientific calculator; any other material (books, notes, etc.) is forbidden. To pass the exam, students must receive at least 15 out of 30 in both parts of the written test. If the final mark (that is the average of the grades obtained in the two parts of the written test) is less the 18 out of 30, the student is required to sit for an oral examination. Contents, assessment methods and criteria are the same for all students and do not depend on the number of classes attended.

A noncompulsory intermediate test on the first part of the program (typically on descriptive statistics and a part of probability) is planned for the beginning of November. The passing of this intermediate test can entail an increase of at most three points of the result obtained in the written test (if the written test is taken and passed in one of the two winter examination sessions).

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

## Teaching materials e documents

- 01) Informazioni sul corso (pdf, it, 64 KB, 20/09/17)
- 02) Commissioni di esame A.A. 2017-2018 (pdf, it, 262 KB, 20/09/17)

## 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 soon also via the Univr app.

## Graduation

## List of theses and work experience proposals

theses proposals | Research area |
---|---|

Tesi di laurea - Il credit scoring | Statistics - Foundational and philosophical topics |

La performance delle imprese che adottano politiche di Corporate Social responsibility | Various topics |

La previsione della qualita' dei vini: Il caso dell'Amarone | Various topics |

Proposte di tesi | Various topics |

Tesi in Macroeconomia | Various topics |

tesi triennali | Various topics |