Lecture
This lecture covers the graphical analysis of full factorial experiments, focusing on the interpretation of main effects, interactions, and mean effects. It explains how to efficiently analyze data, avoid errors due to poor baselines, and conserve degrees of freedom. The instructor uses a balloon example to illustrate the concepts, emphasizing the importance of testing all combinations and choosing appropriate baselines. Various plots, such as scatter plots, mean plots, and block plots, are discussed to identify important factors, optimal settings, and outliers. The lecture concludes with an explanation of interaction effects and how to interpret them using an interaction effects matrix.