Spring School 2018

Design and Analysis of Experiments


Design of experiments or DOE is a key tool for product and process improvement and innovation. However, experimenters often have to deal with a mismatch between standard experimental designs, such as factorial and fractional factorial designs, central composite designs, and the features of their problems. This course motivates the standard and routine use of a fully flexible approach to design of experiments, named optimal design of experiments, by showing its application in ten case studies covering a wide range of practical situations. The increasing computing power and the availability of user-friendly software for the tailor-made design of experiments has made optimal experimental design a key tool for researchers, engineers and statistician in the 21st century. This course will demonstrate the usefulness of optimal design of experiments in a wide variety of contexts, and discuss the analysis of the data produced by the experiments. Throughout, the introduction of new concepts, JMP demos and exercises are intertwined. The JMP software will be available to all participants.

The course will deal with screening experiments, response surface experiments and mixture experiments, and show how to take into account practical complications such as constraints on the factor levels, the need for blocking, the availability of covariate information concerning the experimental units, and difficulties to randomize the experimental tests. Blocked experiments, split-plot experiments and strip-plot experiments will therefore be key topics.

While the concepts and theory will be explained in detail, this is a hands-on course aimed at applying optimal experimental design and analyzing data, rather than a course on optimal design theory. Therefore, the Spring School 2018 complements the Summer School 2018, where the emphasis is more on the theory rather than on the application.


All sessions will be taught by Peter Goos, a full professor at the Faculty of Bio-Science Engineering of the University of Leuven and at the Faculty of Applied Economics of the University of Antwerp, who teaches various introductory and advanced courses on statistics and probability. His main research area is the statistical design and analysis of experiments. He is an author of the book “Optimal Design of Experiments: A Case Study Approach“, on which the course is based.

Course materials

Handouts will be made available beforehand in electronic form. The textbook “Optimal Design of Experiments: A Case Study Approach” can be bought at a discount price when registering.


The 2018 Spring School on Design of Experiments will take place in Leuven from 4th till 6th April 2018. Registration will start at 10.30 am on April 4. The school will end at 3 pm on April 6.


The lecture room is located at University of Leuven – Van den Heuvel Instituut, Dekenstraat 2, 3000 Leuven (VHI 01.22), which is right in the town center.

Travel information

Leuven is easy to reach by train from the Brussels train stations (roughly 20-30 minutes), from Liège (30 minutes) and from the Brussels national airport (15 minutes by train). Note that the Brussels South airport is further.


The best thing to do is to seek accommodation in the town center: everything within the town center is at most 1 km from the lecture room. The youth hostel is also within walking distance. Hotels near the train station are cheaper than those in the town center, and still within walking distance of the lecture room. Registrants can find information about places to stay on the website of the town of Leuven.


  • 175 € – PhD students
  • 250 € – other academics and attendees from non-profit organisations
  • 750 € – other
  • 10 € – invoice


With invoice

Register now

Without invoice

Register now