Lecture
This lecture covers the types of designs used in experiments, such as screening designs to identify important factors and response surface designs to optimize significant factors. It explains the concept of half-factorial designs to reduce the number of experiments. Examples illustrate balanced designs and exploiting redundancies in interactions. The lecture also discusses the analysis of fractional factorials, model building, and graphical checks for data validity. It concludes with a revision of the model building process and the interpretation of box plots to understand the effects of different factors.