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This lecture introduces fractional factorial designs as a method to reduce the number of experiments needed to study interactions between factors. The instructor explains the concept of aliasing in the design matrix, the geometric interpretation of fractional factorial designs, and the importance of selecting significant effects. Through examples, the lecture demonstrates how to identify main effects and interactions in a chemical reactor experiment. The lecture also covers the generation of fractional factorial designs, the resolution of the design, and the interpretation of normal plots. Overall, the lecture provides a comprehensive overview of how fractional factorial designs can efficiently reveal important interactions in experimental studies.