By Russell Schwartz
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Extra info for Biological Modeling and Simulation - A Survey of Practical Models, Algorithms, and Numerical Methods
Runs 1 2 3 4 5 6 7 8 A B C Step 3: Write out all of the two-factor interactions and the three-factor interactions. 4, they are AB, AC, BC, and ABC. Step 4: Confound any remaining main effect with a two-factor interaction or a three-factor interaction. 4, D AB, E AC, F BC, and G ABC. Step 5: Design the experiment with all factors. 4, the analyst ran the following resolution III design. 10. 5. 11 below. 11. 5 These results clearly suggest that the resist thickness (A) and the exposure (C) have a significant effect on circuit board etching.
A two-level full factorial design requires at least 2 8 experimental runs. Designing and Conducting the Experiment Run 1 2 3 4 5 6 7 8 A B + 21 C Y 26 35 40 50 42 38 57 42 The goal of this experiment is to determine which factors affect the life of the machine tool and to recommend the levels of the important factors that maximize the life of the machine tool. The main effect of cutting speed is A , the main effect of tool geometry is B and the main effect of cutting angle is C The effect of cutting speed is zero; this suggests that the cutting speed does not affect the life of the machine tool.
A BC Response 9 6 6 9 Obviously, both columns will result in exactly the same values. Next we present the most useful two-level fractional factorial designs. B. Fractional Factorial Designs of Resolution III Fractional factorial designs of resolution III are designs in which no main effects are confounded with any other main effect. However, main effects are confounded with two-factor interactions and two-factor interactions may be confounded with each other. Fractional factorial designs were first introduced by Finney .
Biological Modeling and Simulation - A Survey of Practical Models, Algorithms, and Numerical Methods by Russell Schwartz
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