Design of experiments (DoE)

€ 2.305 excl. VAT
4 days
In English on request

During this course you will gain knowledge and skills in the application of statistical techniques for the design of experiments and the analysis of the data obtained.

DoE: Practical methods to discover and interpret relationships between factors

Experiments play an important role in understanding and controlling systems and processes. With the aid of methods for statistical design of experiments, it is immediately possible to set up these experiments efficiently and to analyze and interpret their results.

It is important to formulate a clear problem description, identify important influencing factors and choose the right experimental techniques. It is equally important to determine how many experimental runs are needed and which factor combinations should be measured.

Principles of experimental design are successfully applied in a wide variety of areas, but especially in industry, where experiments becoming increasingly important to analyze and to improve processes.

Statistical techniques for experimental design and data analysis

This DoE-course:

  • Provides knowledge and skills in the application of statistical techniques for experimental designs.
  • Gives you experience in analyzing the data obtained.
  • Teaches you to apply the methods discussed independently in your own work environment.
  • Teaches you to use relevant statistical software such as R in a responsible way.

Intended for

Process, product or quality engineers and other technicians and scientists involved in the development and optimization of processes and products. The course is also suitable for lecturers from universities and colleges of higher education who want to learn more about design of experiments and data analysis.

Knowledge of basic statistical techniques such as testing, estimation and regression modelling is desirable, as is some experience in the use of (elementary) linear algebra and statistical software.
Enige ervaring in het gebruik van (elementaire) lineaire algebra en van statistische software is wenselijk.
Praktische voorbeelden zijn in R.

The techniques demonstrated with R, can also be performed in Python and yield comparable results. Participants receive sample data files so that they can reproduce the results using their preferred data analysis software. It is possible to use R from Python and Python from R and combine the advantages of each. Do you want to use Python or discover more possibilities of Python? View our course Python for engineers.

In English on request

Do you want to follow the course in English? Please mention this in the remarks field when you register.

Course leader

Data analysis and programming

dr. Koo Rijpkema

Eindhoven University of Technology (TU/e)

“For me, teaching means sharing knowledge and passion, inspiring and fascinating people through the application of statistics.”

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  • The latest post-academic knowledge and skills
  • Focused on questions that arise in a technical environment
  • Interactive and directly applicable in practice
  • Top teachers from science, research and business

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Upcoming dates

Design of experiments (DoE)

Startdatum: 8 January 2025
Locatie: Omgeving Utrecht
Prijs: € 2.305 excl. VAT

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  • "Strong background on the theory of DOE and justification for the method itself. Allowing to explain the reasoning behing experimental design."
    Participant working in a chemical manufacturing company
  • "Good amount of repetition, thorough deep build-up, nice energetic presentation."
    Participant working in a chemical manufacturing company
  • "Good theoretical foundation to what I employed over the years."
    Participant working in a chemical manufacturing company

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