Bachelor's degree in Economics, Firms and International Markets

Data Analysis Laboratory with R (Vicenza)

Course code
4S009618
Name of lecturer
Marco Minozzo
Coordinator
Marco Minozzo
Number of ECTS credits allocated
3
Other available courses
Academic sector
NN - -
Language of instruction
Italian
Period
not yet allocated

Learning outcomes

The course "Data Analysis Laboratory with R" 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.

- Due to the COVID-19 emergency, this year lessons will be delivered online through Zoom meetings. Each course has, approximately, 50 places.

- There will be two courses, one in the first semester and another one in the second semester.

- Requests for participation will be considered following the registration order, considering that priority will be given to CdLM students, in particular to students of the Master’s degree in International Economics and Business. Students are required to be present at the first lesson, or to send an email to the tutor to communicate 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 calendar of the course of the first semester will be available as soon as possible.

The calendar of the course of the second semester will be available as soon as possible.

Tutor (first semester): dott. Luca Bisognin
Tutor (second semester): to be announced


For the course of the first semester, it is possible to register from the 13th of October 2020 to the 18th of October 2020.

For the courses of the second semester, it is possible to register from the 13th of October 2020 to the 28th of February 2021.

Please, register through the elearning platform (Moodle). Students without a university IT account can ask to be registered by writing an email to the coordinator of the course. All other students must use the procedure on Moodle.

Syllabus

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 16000 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.

Reference books
Author Title Publisher Year ISBN Note
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

Assessment methods and criteria

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, which will take place online through a Zoom meeting, will consist in a written exam, followed by an oral examination, if necessary, on the use of the software R. There will be just one date for the final examination.



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