In this course students will learn how to easily adapt their daily practice to a more rigorous experimental and analytical approach. The students will learn how to perform experiments efficiently with maximum result.
2. Description of the Course Goals: Increase sensitivity for doing experiments in an efficient and effective way. Getting to know how to analyze data Exploring the possibilities to optimize processes Means: Presentation in the group Experimental intermezzo’s Homework + feedback Take own case Structure: Half-day sessions 5 – 6 sessions, spread over 5 – 6 weeks. Level: to be discussed; the character of the training will be adapted to the conceptual level expected.
3. Layout of the course Session 1: Introduction to experimenting Purpose Variables Experiments Full factorial 2^N example Session 2: Experimental options and analyses Options (confounding and partial factorial schemes) Analyses (strategy, ANOVA) Session 3: Expanding and alternative experiments Continued: analyses (outliers, multiple regression) Statistical model en optimalisation CCD and Box-Behnken Session 4: Taguchi Philosophy Original approach Advantages/disadvantages Integration with classical methods: robust design Session 5: Own case
