Course ObjectiveThe course focuses on:
1) Processing and analyzing datasets relevant for TSCM by using the
software tool R.
2) Describing research results and drawing managerial conclusions.
3) Analyze, formulate and solve data analytics problems.
4) Apply and compare well-known data analytics methods from the
5) Analyze real-life case studies by using the knowledge acquired
throughout the course.
6) Provide and defend managerially relevant recommendations to decision
Course ContentSupply Chain Data Analytics is focused on furnishing you with
methodological and technical skills to conduct data driven research in
academic and industry projects in the TSCM domain. The main topics of
the course are time series forecasting, regression, classification and
clustering. The software tool R will be used to process and analyze the
Method of AssessmentComputer exam entry requirements R - Individual assessment
Written exam - Individual assessment
Assignment - Group assessment
Entry RequirementsBasic knowledge of statistics (descriptive statistics, correlation, and
regression) and R is required. If you do not have experience with R make
sure to learn the basics (installing classes, syntax, data types,
importing data and descriptive statistics) of R before the start of this
LiteratureShmueli, G., & Lichtendahl, K. C. (2016). Practical Time Series
Forecasting with R: A Hands-On Guide. Axelrod Schnall Publishers (Second
Additional material will be provided via Canvas.
Target AudienceThis is a course for TSCM students only; non-TSCM students (including
exchange students) cannot take this course unless explicit approval is
obtained from the course coordinator beforehand.
|Language of Tuition||English|
|Faculty||School of Business and Economics|
|Course Coordinator||dr. D.D. Tönissen|
|Examiner||dr. D.D. Tönissen|
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Study Group, Lecture|
This course is also available as: