Course Introduction to R


Course leader: Rodrigo Labouriau

Language: English

Graduate school: Course collaboration

Course fee: 1,200.00 DKK

Status: Course is open for application

Semester: Fall 2022

Application deadline: 25/09/2022

Start date: 25/10/2022

Administrator: Thilde Møller Risgaard

The course Introduction to R is offered by the Graduate School of Natural Sciences/GSNS and Graduate School of Technical Sciences/GSTS, Aarhus University, fall 2022.

Name of course: Introduction to R

ECTS credits: 1.0 ECTS

Course parameters: No. of contact hours/hours in total incl. preparation, assignment(s) or the like: 12 hours confrontation + 12 hours self study. Capacity limits: Minimum 10 and maximum 20 participants

Objectives of the course:
The aim of the course is to introduce the student to the basic use of the software R. The course is designed to build up the basic skills in R necessary for attending to the PhD course Basic Statistical Analysis.

Learning outcomes and competences:
At the end of the course, the student should be able to:

Read and write data in R, perform basic operations with variables, vectors, make simple tabulations, use and create simple functions, use repeated and conditional calculations, reshape and merge data sets, draw simple graphs in R, and use and install packages in R.

Compulsory programme:
The participants will solve a collection of simple programming exercises in the last part of the course. These exercises involve some very basic notions of statistics (explained during the course, no background of statistics is required), but are primarily exercises on simple programming with R.

Course contents:

1 – Introduction to edition in an R environment

2 – Basic data structures in R

3 – Methods to read and write data in R

4 – Basic calculations and manipulations of data in R

5 – Simple descriptive statistics and graphical representation of data in R

6 – Installing and using packages in R.

It is assumed that each student works on her/his own computer. The PhD students should install the program R and Rstudio on their computers before the course starts.

Name of lecturer: Rodrigo Labouriau

Type of course/teaching methods:
Lectures interlaced with practical exercises and homework.

Literature and course material:
A collection of tutorials and demonstration programs distributed (for internal use only) during the course.

Course homepage:

Course assessment:
Attendance threshold (80%).

Applied Statistics Laboratory (aStatLab) at the Department of Mathematics, Aarhus University in collaboration with the GSNS. Course responsible: Rodrigo Labouriau (aStatLab, MATH AU).

25th and 26th October 2022 (week 43)

Department of Mathematics if held physically otherwise online. If held physically the course will not be simultaneously transmitted online.

No show fee:
Course participants on our transferable skills courses, who do not show up at the course or cancel their course participation after the course cancellation deadline (without providing a doctor’s note), may have to pay a no-show fee, unless someone from the waiting list is able to take part in the course instead.

The no-show fee is DKK 1,200 (the price of one ECTS). The no-show fee has been introduced due to many late cancellations, thus preventing people from the waiting lists to have a seat at the courses.


  • Participation in the course is without cost for PhD students from Aarhus University

Due to an Agreement between Danish Universities coming into force as of 1 January 2011, participants from other universities than Aarhus University will have to pay DKK 1,200 per ECTS. In principle this also applies to external parties, but exemption can be granted under specific circumstances.

Please be aware that your registration for the course not necessarily equals your admission for the course. You will receive an e-mail after the registration deadline regarding whether you are admitted for the course or if you are registered on the waiting list. Please note that seats are allocated on a first-come-first-served basis.

Course dates:

  • 25 October 2022 09:15 - 15:00
  • 26 October 2022 09:15 - 15:00