The article "An Application of Fractional Factorial Designs" (M. Kilgo, Quality Engineering, 1988:19-23) describes a25-1 design (half-replicate of a 2 design) involving the use of carbon dioxide (CO,) at high pressure to extract oil from peanuts. The outcomes were the solubility of the peanut oil in the CO, (in mg oil/liter CO,), and the yield of peanut oil (in percent). The five factors were A: CO, pressure, B: CO, temperature, C: peanut moisture, D: CO, flow rate, and E: peanut particle size. The results are presented in the following table. Treatment Solubility Yield 29.2 63 23.0 21 37.0 36 abe 139.7 99 23.3 24 ace 38.3 66 bce 42.6 71 abc 141.4 54 d. 22.4 23 ade 37.2 74 bde 31.3 80 abd 48.6 33 cde 22.9 63 acd 36.2 21 bed 33.6 44 abcde 172.6 96 Assuming third- and higher-order interactions to be negligīble, compute estimates of the main effects and interactions for the solubility outcome. a. Plot the estimates an a normal probability plot. Does the plot show that some of the factors influence the solubility? If so, which ones? b. Assuming third- and higher-order interactions to be negligible, compute estimates of the main effects and interactions for the yield outcome. C. d. Plot the estimates on a normal probability plot. Does the plot show that some of the factors influence the yield? If so, which ones?

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The article "An Application of Fractional Factorial Designs" (M. Kilgo, Quality
Engineering, 1988:19-23) describes a25-1 design (half-replicate of a 2 design) involving
the use of carbon dioxide (CO,) at high pressure to extract oil from peanuts. The outcomes
were the solubility of the peanut oil in the CO, (in mg oil/liter CO,), and the yield of peanut
oil (in percent). The five factors were A: CO, pressure, B: CO, temperature, C: peanut
moisture, D: CO, flow rate, and E: peanut particle size. The results are presented in the
following table.
Treatment
Solubility
Yield
29.2
63
23.0
21
37.0
36
abe
139.7
99
23.3
24
ace
38.3
66
bce
42.6
71
abc
141.4
54
d.
22.4
23
ade
37.2
74
bde
31.3
80
abd
48.6
33
cde
22.9
63
acd
36.2
21
bed
33.6
44
abcde
172.6
96
Assuming third- and higher-order interactions to be negligīble, compute estimates of
the main effects and interactions for the solubility outcome.
a.
Plot the estimates an a normal probability plot. Does the plot show that some of the
factors influence the solubility? If so, which ones?
b.
Assuming third- and higher-order interactions to be negligible, compute estimates of
the main effects and interactions for the yield outcome.
C.
d.
Plot the estimates on a normal probability plot. Does the plot show that some of the
factors influence the yield? If so, which ones?
Transcribed Image Text:The article "An Application of Fractional Factorial Designs" (M. Kilgo, Quality Engineering, 1988:19-23) describes a25-1 design (half-replicate of a 2 design) involving the use of carbon dioxide (CO,) at high pressure to extract oil from peanuts. The outcomes were the solubility of the peanut oil in the CO, (in mg oil/liter CO,), and the yield of peanut oil (in percent). The five factors were A: CO, pressure, B: CO, temperature, C: peanut moisture, D: CO, flow rate, and E: peanut particle size. The results are presented in the following table. Treatment Solubility Yield 29.2 63 23.0 21 37.0 36 abe 139.7 99 23.3 24 ace 38.3 66 bce 42.6 71 abc 141.4 54 d. 22.4 23 ade 37.2 74 bde 31.3 80 abd 48.6 33 cde 22.9 63 acd 36.2 21 bed 33.6 44 abcde 172.6 96 Assuming third- and higher-order interactions to be negligīble, compute estimates of the main effects and interactions for the solubility outcome. a. Plot the estimates an a normal probability plot. Does the plot show that some of the factors influence the solubility? If so, which ones? b. Assuming third- and higher-order interactions to be negligible, compute estimates of the main effects and interactions for the yield outcome. C. d. Plot the estimates on a normal probability plot. Does the plot show that some of the factors influence the yield? If so, which ones?
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