Experimental Design
This course discusses the design of factorial experiments. Initially, the focus is on completely randomized experimental designs. Next, the focus shifts to experimental designs involving a restricted randomization. First, the concept of blocking is discussed. Next, split-plot and strip-plot designs are studied.
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- Prerequisites: knowledge of basic statistics, regression analysis, and matrix algebra
- Price: €220-€1100
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The emphasis in the course is on the optimal design of experiments. In optimal design of experiments, the experimental design is tailored to the problem at hand (unlike classical experimental design, where standard designs from catalogs are chosen).
The course builds on concepts from regression and analysis of variance, such as fixed and random effects, power calculations, variance inflation factors, multicollinearity, confidence intervals, prediction and lack-of-fit tests.
Every topic in the course is introduced and illustrated by means of a case study from industry. The case studies are realistic in the sense that they involve quantitative and qualitative experimental factors, experimenters have to deal with limited budgets and difficulties to randomize, and forbidden combinations of factor levels. In each of the case studies, the goal is to enhance to performance of a process or a product.
The statistical software package used is JMP.