Answer the questions a and b in the text.
• In answering part a, I would like you to look at all effects that you can estimate, and then work towards determining the final model that you think would be most appropriate for this data. Compare the two approaches to this analysis (Model script and Screening script). You do not need to include all JMP output, but you do need to provide an explanation of what model you looked at initially, what analysis methods you used, and how you arrived at your final model.
• For part b, note that the run order is given. Include in your report all the residual plots that you make, and their interpretation. If a transformation is called for, what transformation do you think would be appropriate? Why?
In addition to parts a and b above, answer the following questions. (Hint: See Table 7.9 in the text, or use the Screening Design option in JMP to set up these designs and then create a column of Y data you can analyze to see what you get).
c. If this design had to be run in 2 blocks of 8, what would be the best way to do this? What would we “lose” by blocking this way? Explain your answer.
d. Instead, if this design had to be run in 8 blocks of 2, what would be the best way to do this? What would we “lose” by blocking this way? Explain your answer.
And then also answer the following questions.
e. Can we tell if there is curvature in the response (curvature relative to one of the x variables) with this design? Why or why not.
f. Suppose we would like to run a follow-up experiment to this one, to try to lower UEC even further towards the theoretical minimum of 0. Which variables should be included, and what specific design and variable levels would you recommend using? Explain your reasoning for the design and levels that you recommend.
Please include relevant JMP output with this assignment – you don’t need to comment on everything.
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