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
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.
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° 3° | Soft skills coaching days Vicenza | D |
Paola Signori
(Coordinator)
|
| 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)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° 3° | Simulation and Implementation of Economic Policies | D |
Federico Perali
(Coordinator)
|
| years | Modules | TAF | Teacher |
|---|---|---|---|
| 1° 2° 3° | Parlare in pubblico e economic writing | D |
Martina Menon
(Coordinator)
|
Data Analysis Laboratory with R (Vicenza) (2019/2020)
Teaching code
4S009145
Teacher
Coordinator
Credits
3
Also offered in courses:
- Data Analysis Laboratory with R (Vicenza) of the course Bachelor's degree in Business Administration (Vicenza)
- Data Analysis Laboratory with R (Vicenza) of the course Master's degree in International Economics and Business Management
- Data Analysis Laboratory with R (Vicenza) of the course Master’s degree in Management and business strategy
- Data Analysis Laboratory with R (Vicenza) of the course Master’s degree in Business Management (Vicenza)
Language
Italian
Scientific Disciplinary Sector (SSD)
NN - -
Period
Not yet assigned
Learning outcomes
The course "Data Analysis Laboratory with R (Vicenza)" is an optional "type f" activity, which allows to students to obtain 3 CFU, once a final examination is passed. In particular:
- The course is open to all CdL and CdLM students of the Vicenza campus of the School of Economics and Management.
- The lessons will take place in a computer laboratory (40 seats).
- Requests for participation will be considered following the registration order considering that priority will be given to CdLM students. Students are required to be present at the first lesson, or to send an email to the tutor to comunicate their absence.
- Participation to the course does not require any particular background knowledge of the software R.
- The frequency to the classes is compulsory. Students are required to attend at least 2/3 of the exercise lessons and tutorial activities in order to be admitted to the final evaluation.
The course consists of 18 hours of exercise lessons and tutorial activities (plus 2 hours of final examination).
The tentative calendar of the course is the following:
Thursday 5 March 2020, hours 14:00-17:30, computer laboratory;
Thursday 12 March 2020, hours 14:00-17:30, computer laboratory;
Wednesday 18 March 2020, hours 9:00-12:30, computer laboratory;
Thursday 26 March 2020, hours 14:00-17:30, computer laboratory;
Thursday 2 April 2020, hours 14:00-18:00, computer laboratory;
Wednesday 8 April 2020, hours 10:00-12:00, computer laboratory (final exam).
Tutor: dott. Alessandro Cipolla
Registrations are open from the 27th of February 2020 to the 8th of March 2020.
Please, register through the elearning platform.
Program
R is an open-source software for statistical computing. Created at the end of the 1990s from the S software, R is a multi-paradigm language that over the course of two decades has acquired a central role among statistical software, thanks also to the development of more than 15000 packages implementing techniques and methods coming from the most diverse fields of methodological and applied statistics. In recent years, thanks to the development of an entire family of packages aimed at simplifying and organizing on a new basis the programming methods and the interaction with R, the software has found new opportunities to express its potential to the fullest. The R language, together with Python, is now considered the reference language in modern data science and, in particular, for machine learning. It easily interfaces with many other software such as Excel, Tableau, Microsoft Power BI etc.
The course aims to provide the basics of the programming and operating philosophy of the R software, introducing the participants to some of the most recent innovations. After the introduction of the R language and of R Studio (the most used IDE for R), the course will focus on the following topics: data processing and manipulation techniques, advanced graphical tools for statistical analysis, graphic representation of geo-referenced information, regression analysis, Monte Carlo simulations, automatic reporting and production of interactive documents.
| Author | Title | Publishing house | Year | ISBN | Notes |
|---|---|---|---|---|---|
| Hadley Wickham | Advanced R (Edizione 1) | CRC Press, Taylor & Francis Group | 2015 | 9781466586970 | |
| Espa G., Micciolo R. | Analisi esplorativa dei dati con R | Apogeo | 2012 | 978-88-503-3031-7 | |
| Ronald K. Pearson | Exploratory Data Analysis Using R (Edizione 1) | CRC Press, Taylor & Francis Group | 2018 | 9781138480605 | |
| Marco Bee, Flavio Santi | Finanza quantitativa con R (Edizione 1) | Apogeo Education | 2013 | 9788838787041 | |
| Hadley Wickham | ggplot2: Elegant Graphics for Data Analysis (Edizione 1) | Springer | 2009 | 9780387981413 | |
| Francesca Ieva, Chiara Masci, Anna Maria Paganoni | Laboratorio di Statistica con R (Edizione 2) | Pearson | 2016 | 9788891901521 | |
| Giuseppe Espa, Rocco Micciolo | Problemi ed esperimenti di statistica con R (Edizione 1) | Apogeo Education | 2013 | 9788838786105 | |
| Hadley Wickham, Garrett Grolemund | R for Data Science (Edizione 1) | O'Reilly | 2016 | 9781491910399 | |
| Ngai Hang Chan, Hoi Ying Wong | Simulation Techniques in Financial Risk Management (Edizione 1) | Wiley | 2015 | 9781118735817 | |
| M. Bécue-Bertaut | Textual Data Science with R (Edizione 1) | CRC Press, Taylor & Francis Group | 2018 | 9781138626911 | |
| Graham J. Williams | The Essentials of Data Science: Knowledge Discovery Using R (Edizione 1) | CRC Press, Taylor & Francis Group | 2017 | 9781138088634 |
Examination Methods
Students are required to attend at least 2/3 of the exercise lessons/tutorial activity in order to be admitted to the final evaluation. The final examination will consist in a written exam, with an oral examination if necessary, on the use of the software R. There will be just one date for the final examination.
