Date: June 15, June 29 and July 6
Time: 15:00 - 16:00 BST | 16.00 – 17.00 CEST
Mastering the fundamentals of Statistical Design and Analysis of Experiments (“DOE”) enables you to ensure effectiveness and efficiency in your empirical learning across various science and engineering situations. But you will soon have questions about how to solve more complex problems using DOE.
In this series of webinars, you will learn about designs that go beyond “classical” factorial and fractional factorial designs. You will see how optimal designs can be tailored to the practical constraints of your process or system.
You will learn about methods for maximising your insight when time is a variable or you have “curve” responses. And you will learn more about sequential approaches to experimentation, including newer approaches like Bayesian optimisation.