B2023 - R FOR ECONOMISTS

Academic Year 2025/2026

  • Teaching Mode: Traditional lectures
  • Campus: Bologna
  • Corso: Second cycle degree programme (LM) in Applied Economics and Markets (cod. 6756)

    Also valid for Second cycle degree programme (LM) in Economics and Public Policy (cod. 6758)

Learning outcomes

This course provides theory and tools for using R as a programming language in economic research, for the purposes of visualizing and analyzing data.

Course contents

Introduction to R and RStudio.

Arithmetics, mathematics and logic in R. Data structures in R.

Creation and management of variables and dataframes. Data importing.

Descriptive analysis of data and graphical representations.

Statistical inference for the mean of a gaussian population and for a proportion.

Comparison of means of two population.

Linear regression.

Readings/Bibliography

The following books are freely available on the internet.

Wickham, Hadley, and Grolemund, Garrett. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. Stati Uniti, O'Reilly Media, 2016. https://r4ds.had.co.nz

Måns Thulin, Modern statistics with R, 2021. http://modernstatisticswithr.com/

Teaching methods

Class lectures.

Each student will need to bring his/her own laptop after installing R and RStudio in this order:

install R from http://cran.r-project.org/

install RStudio from http://rstudio.org/download/desktop

Assessment methods

The exam will be in writen format and at the end of the course the students will have to do a final presentation which will count to the overall grade.


Grading policy insufficient <18; sufficient 18-23; good 24-27; very good 28-30; excellent 30 cum laude.


Grade Rejection Policy

Students are allowed to reject the grade obtained in an exam once. To do so, they must send an email request to the instructor within the deadline set for grade registration. The instructor will confirm receipt of the request by the same deadline.

Teaching tools

Students with disability or specific learning disabilities (DSA) are required to make their condition known to find the best possibile accomodation to their needs.

Office hours

See the website of Adelajda Matuka

SDGs

Quality education

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.