Kies de Nederlandse taal
Course module: ECB2PR
Programming with R
Course infoSchedule
Course codeECB2PR
ECTS Credits7.5
Category / Level2 (2 (Bachelor Elaborating))
Course typeCourse
Language of instructionEnglish
Offered byFaculty of Law, Economics and Governance; Undergraduateschool REBO; Bachelor in Economics and Business Economics;
Contact persondr. M.J.L.F. Cruyff
Course contact
dr. M.J.L.F. Cruyff
Other courses by this lecturer
Teaching period
3  (08/02/2021 to 25/04/2021)
Teaching period in which the course begins
Time slotB: B (TUE-morning, THU-afternoon)
Study mode
RemarkDedicated minor course
Enrolment periodfrom 02/11/2020 up to and including 29/11/2020
Course application processOsiris Student
Enrolling through OSIRISYes
Enrolment open to students taking subsidiary coursesNo
Post-registration openfrom 25/01/2021 up to and including 26/01/2021
Waiting listNo
Course goals
Learning objectives 
After successfully completing this course, you are able to:
•      distinguish between R data structures;
•      import, manipulate and visualize data;
•      analyse data with the linear model;
•      program basic functions (e.g. bootstrapping);
•      report their work in dynamic R Markdown documents.
This course is part of the minor Applied data science for Economists.
R is statistical software environment that is currently the world's standard for data analysis and visualization. The main advantage of R is that it is extendable with countless packages that allow for any conceivable statistical procedure in a user-friendly way. RStudio is an IDE for R that includes extra functionality that makes it even more easy to work with R, such as a sophisticated text editor and debugger, integrated help, additional tools for plotting and making dynamic R Markdown documents. In this course you learn the basic data structures of R, data exploration, manipulation and visualization with the state-of-the-art R packages tidyverse and ggplot2, data analysis with the linear model, some functional programming, and how to present their work in R Markdown documents.

Each week there will be one lectures and one practical. This course will be following the BYOD (bring your own device) principle: you have to bring their own laptop to the meetings.

Academic skills
This course focuses on the following academic skills:
  • Analytical skills
    • ​Problem solving (identifying the problem, devising a path towards the solution, following this path, verifying the outcome) for specific questions
Assessment method
Individual assignment (40% of the grade) and an exam (60% of the grade) at the end of the course.

Effort requirement 
Attendance of at least 80% of the meetings.

Study materials:
•      Chapters from various online textbooks (freely available on internet)

Courses that build on Introduction to  programming in R:
•      Applied Data Analysis and Visualization I for Economists
•      Applied Data Analysis and Visualization II - unsupervised learning
For UU students only, no exchange students this year.
Assumed Knowledge
You are expected to have knowledge of:
•      Mathematics for Economists (ECB1WIS)
•      Introduction to Applied Data Science (ECB1ID)

In case online access is required for this course and you are not in the position to buy the access code, you are advised to contact the course coordinator for an alternative solution. Please note that access codes are not re-usable meaning that codes from second hand books do not work, as well as access codes from books with a different ISBN number. Separate or spare codes are usually not available.
Entry requirements
You must meet the following requirements
  • Enrolled for a degree programme of faculty Faculty of Law, Economics and Governance
Prerequisite knowledge
You are expected to have knowledge of:
• Mathematics for Economists (ECB1WIS)
• Introduction to Applied Data Science (ECB1ID)
Required materials
Recommended materials
Yet to be specified
Instructional formats


Test weight40
Minimum grade1

Test weight60
Minimum grade1

Kies de Nederlandse taal