Statistics and Design of Experiments

• Descriptve Statistics: cf. Teaching
• Inferential Statistics: cf. Teaching
• DoE – Design of Experiments: cf. Teaching

My Interest!

Describe a statistical example / problem, e.g. by email. We will help with a hint or a comparable example. To be able to explain the background in more detail, we recommend a course in which the solution is covered.

• Example 1: During quality control, screws arrive at different temperatures. Is there an influence of temperature on the strength of the screws and how can I take this into account? A regression can help here. What the coefficient of determination R2 means and why it is important is covered in the Descriptive Statistics course.

• Example 2: The strength of a wire grade is about 404 N/mm² but varies (standard deviation 13.2 N/mm²). What strength can be guaranteed – to the customers – at a 99% level? In 99% of the cases the strength is greater than 373 N/mm². The topic of confidence intervals is covered in the course Inferential Statistics.
• Example 3: Employees present 4 possible parameters whose 3 different settings on a production line could improve the quality of the products. What is the quickest way to find out which parameters improve quality and which do not? That a Taguchi L9 experimental design with only 9 experiments (instead of testing all 81 possible parameter combinations) can help here, and what it does not take into account, is explained in the Design of Experiments course.

Selected Projects