Question: A 2 4 factorial design was run in a chemical process. The design factors are A = time, B = concentration, C = pressure, and

A 24factorial design was run in a chemical process. The design factors are A = time, B = concentration, C = pressure, and D = temperature. The response variable is yield. The data follow:

Factor Levels Yield (pounds) Run A B C D A (hours) 12 2 3 18 B (%) 14 18 C (psi) 13 80 16 D (°C) 200 250 4 17 15 6. 20

(a) Estimate the factor effects. Based on a normal probability plot of the effect estimates, identify a model for the data from this experiment.

(b) Conduct an ANOVA based on the model identified in part (a). What are your conclusions?

(c) Analyze the residuals and comment on model adequacy.

(d) Find a regression model to predict yield in terms of the actual factor levels.

(e) Can this design be projected into a 23 design with two replicates? If so, sketch the design and show the average and range of the two yield values at each cube corner. Discuss the practical value of this plot.

Factor Levels Yield (pounds) Run A B C D A (hours) 12 2 3 18 B (%) 14 18 C (psi) 13 80 16 D (C) 200 250 4 17 15 6. 20 15 8. 10 10 25 11 13 12 24 13 19 14 21 15 17 16 23 | +I + I + |

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