Content description

In an ideal world, there might be a single thing that causes something to happen. And we would even know relationship this 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 a broad sense, experimentation can be separated into two categories. One is to screen potential factors to find out which of those are of practical importance. Category two is to optimize the most important factors to the needs of your research question. This workshop will cover both screening and optimization designs to help you better designing your experiments.

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.

 

Course content

• • ANOVA and contrasts
  • Full and Fractional Factorial Designs
  • Optimal Designs
  • Split-Plot Designs
  • Response-Surface
  • Box-Behnken Designs
  • Central Composite Designs
  • Placket-Burman Designs
  • Taguchi Designs
  • Mixture Designs

 

Dates

June 15, 2023 (9.00 am – 4.30 pm)
June 16, 2023 (8.30 am – 3.00 pm)

Please note that we can only give certificates for attending at least 80% of the course.

 

Overview

Trainer	Dr. Peter Paul Heym
Format	Konferenzraum SIZ, Prüferstraße 2, 09599 Freiberg
Fee	no fee for members of the TUBAF
Language	English
Credit Points	0.5
Work unit (AE)	16
Financially supported by	Dr. Erich-Krüger-Stiftung
Registration Deadline	June 8, 2023

 

Registration

Here you can register for the course.
Please fill out each field carefully. Your data will be used for internal processes.

The course can be visited for free. To ensure that others can move up from the waiting list, we would like to ask for your timely deregistration (1 week before the start of the course). We reserve the right to charge the costs of the course proportionally for unexcused absence (without medical certificate).