Design of Experiments
23. November 2021 (09:00 Uhr - 12:30 Uhr)
25. November 2021 (09:00 Uhr - 12:30 Uhr)
30. November 2021 (09:00 Uhr - 12:30 Uhr)
02. Dezember 2021 (09:00 Uhr - 12:30 Uhr)
|Kurssprache / Language||English|
|Leistungspunkte / Credit Points||0,5|
|Arbeitseinheiten (AE) HDS-Zertifikat / work unit (AE) HDS Certificate||16|
|Anmeldeschluss: Registration Deadline||19. November 2021|
|Der Anmeldeschluss ist überschritten. Registration Deadline has been exceeded.|
In an ideal world, there might be a single thing that causes something to happen. And we would even know the relationship because it would be easy to find out using an experiment – an experiment which was easy to set up, elegant to conduct, fast and inexpensive. Not to mention the experiment was accurate… Unfortunately, most scientific questions we are about to investigate are not that straight-forward to answer. Maybe the outcome that you are investigating has more than one potential factor that influences the outcome. And maybe, some of these factors are hard to control or it takes a lot of time, money or material to run your experiment very often. As the number of factors increase it becomes more and more challenging to find out the most important ones or their interaction. This course will focus on the design of experiments so that you can answer your questions of interest, even if there are restrictions in your situation that hinder you from running all combinations. Maybe these requirements do already sound familiar to you.
In this workshop you will get to know commonly used screening and optimization designs. Nowadays computer software will do all calculations for us, but the reasoning behind will be hidden from us. Most of the famous designs like factorial, split-plot or Blackett-Burman designs were invented in times where computer power was not available too much and yet these are very effective, partly because they are almost intuitive to analyze and easy to draw the right conclusions from. In this workshop, using small and interactive examples, we will design and analyze these examples, thereby understanding the purpose, as well as pros and cons of each design. The examples will be analyzed by hand, therefore deepen the understanding.
There is no statistical knowledge necessary to attend this workshop. Still, it would be beneficial to have a basic understanding of ANOVA techniques since this will be the start of our journey through experimentation techniques.
- ANOVA and contrasts
- Full and Fractional Factorial Designs
- Optimal Designs
- Split-Plot Designs
- Box-Behnken Designs
- Central Composite Designs
- Placket-Burman Designs
- Taguchi Designs
- Mixture Designs
Whenever you are interested in successful experimentation, improving the quality of your research by minimizing experimental effort or gain a broader insight into the principles of Design Of Experiments you are very welcome to join this hands-on workshop.