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This lecture covers experimental design strategies such as one-factor-at-a-time, full factorial, and fractional factorial approaches, emphasizing the importance of factors, responses, treatment combinations, replication, randomization, and confounding. It also discusses the interpretation of graphical outputs and the calculation of degrees of freedom and mean squares in experimental results.