Multivariate data analysis

In English on request

During this course you will learn the most common techniques used in an industrial context for the analysis of multivariate data.

Detect patterns and relationships in multiple variable datasets

This course provides knowledge and skills in the application of common statistical techniques used, for example in an industrial context, for the analysis of multivariate data related to quality aspects of products and processes.

The techniques discussed are ideal for discovering relationships between groups of variables, for classifying measurement results or for detecting patterns and clusters in experimental data. Usually, several factors or variables influence the result.

Based on multivariate data analyses, for example, parameter settings in a production process can be related to quality characteristics of the resulting product. They also make it possible to detect combinations of parameter setting where a process becomes unstable or to calibrate a measurement procedure.

Apply multivariate statistical methods

During this course you will learn:

  • Analyze and model variables that are correlated.
  • Identify variables that have a significant influence on a process.
  • Provide options for improved process control.
  • Detect causes of production problems.
  • Apply multivariate methods as discussed independently in your own work situation.
  • Use representative statistical software for multivariate data analysis, such as R, R Studio, Minitab, JMP or IBM-SPSS.

Intended for

Academics, technicians and professionals working in the field of chemometrics, sensory data analysis or quality control of products and processes. The course is also suited for lecturers at universities or colleges of higher education who want to be informed on actual methods for multivariate data analysis.

Kennis van statistische basistechnieken zoals toetsen, schatten en regressiemodellering wordt bekend verondersteld. Enige ervaring in het gebruik van (elementaire) lineaire algebra en van statistische software is wenselijk. Praktische voorbeelden zijn in R.

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.”

This course is rated with an average of


Program manager


  • 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

Frequently asked questions

  • "Goede inleiding in de toepassing van multivariate data analyse, inclusief uitstekende opfrisser van de meer basale statistiek."
    Frank van Boven
    Erasmus MC
  • "Uitstekende cursus, veel aan bod geweest, hoog niveau. Zeer goede, enthousiaste docent."
    Nouryon Industrial Chemicals BV
  • "Interessante diepgaande cursus op hoog niveau, gegeven door een kundige enhousiaste cursusleider."
    Sitech Services BV
  • "Een goede cursus die breed de multivariate analyse toelicht."
    Het Waterlaboratorium
  • "Leerzaam, adaptief, goed voorbereid."
    Joachim Verhagen
    ASML Netherlands BV

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