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B2023 - R FOR ECONOMISTS

Academic Year 2024/2025

                
                        Docente:
                        Adelajda Matuka
                    
                        Credits:
                        6
                    
                        SSD:
                        SECS-S/01
                    
                        Language:
                        English
                    
                        Teaching Mode:
                        Traditional lectures
                        
                            Campus:
                            Bologna
                        
                            Corso:
                            Second cycle degree programme (LM) in
                            Applied Economics and Markets (cod. 5969)

                                Also valid for
                                
                                    Second cycle degree programme (LM) in
                                    
                                        Economics and Public Policy (cod. 5945)
                                    
                                    Course Timetable
                                
from Apr 09, 2025 to May 21, 2025

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 a practical test of data analysis in a computer laboratory.

The structure of the exam will be similar to the one of the examples given in Virtuale.

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

Teaching tools

material provided by the lecturer on Virtuale https://virtuale.unibo.it/
statistical software R https://www.r-project.org/
integrated development environment RStudio www.rstudio.com

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

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