- Docente: Marco Berrettini
- Credits: 2
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: First cycle degree programme (L) in Economics, Politics and Social Sciences (cod. 5819)
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from Sep 21, 2023 to Dec 07, 2023
Learning outcomes
Students develop transversal skills with a focus on the development of skills complementary to the quantitative methods’ courses. In particular, students acquire skills in data analysis and in the use of dedicated software and programming languages such as R or Python, as well as skills in data visualization.
Course contents
R programming:
- user-written functions
- loops
R package tidyverse:
- data manipulation (subsetting, merging, summarising) with dplyr
- data visualization with ggplot2
- web scraping with rvest
R Markdown
Readings/Bibliography
Suggested readings:
Further readings:
- Wickham, H., Çetinkaya-Rundel, M., & Grolemund, G. (2023). R for Data Science. O'Reilly.
- Wickham, H. (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York.
- Xie, Y., Allaire, J. J., & Grolemund, G. (2018). R markdown: The definitive guide. CRC Press.
Teaching methods
Computer laboratory sessions.
In consideration of the type of activity and the teaching methods adopted, the attendance of this training activity requires the prior participation of all students in the training modules 1 and 2 on safety in the study places, in e-learning mode. (https://elearning-sicurezza.unibo.it/)
Assessment methods
Pass/fail exam consisting in a take-home project; group work (max. 4 people) is allowed, accompanied by precise indications about the division of tasks.
The exam aims at evaluating the acquired skills in the use of R for data analysis and visualization.
Although attending classes is not mandatory, it is strongly recommended.
Teaching tools
- R scripts
- Datasets
- Slides
Office hours
See the website of Marco Berrettini