2. A fractional factorial design is employed to investigate effects of five factors on the total...

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2. A fractional factorial design is employed to investigate effects of five factors on the total yield of oil per batch of peanuts (Y). The factor levels are listed in the Table Factor A CO2 Pressure B=CO2 Temperature C-Peanut Moisture D=CO2 Flow Rate E Peanut Particle Size Unit Bar Deg. C % by Weight Liters/minute mm Low Level High Level 415 550 25 95 5 15 40 60 1.28 4.05 For a 16 run experiment, the response values are obtained as tabulated in the Table Treatment Comb (I) ae be ab ce ac bc abce Response values 63 21 36 99 24 66 71 54 Treatment Comb de ad bd abde cd acde bcde abcd Response values 23 74 80 33 63 21 44 96 (a) Identify the design, defining relation and the alias relationships (b) Estimate the main effects for factors (c) Suppose factors B and E are selected to be included in the model. Obtain an ANOVA table. (d) Estimate the regression coefficients for the fitted model (e) Comment on how to analyze residuals to check the model assumptions 2. A fractional factorial design is employed to investigate effects of five factors on the total yield of oil per batch of peanuts (Y). The factor levels are listed in the Table Factor A CO2 Pressure B=CO2 Temperature C-Peanut Moisture D=CO2 Flow Rate E Peanut Particle Size Unit Bar Deg. C % by Weight Liters/minute mm Low Level High Level 415 550 25 95 5 15 40 60 1.28 4.05 For a 16 run experiment, the response values are obtained as tabulated in the Table Treatment Comb (I) ae be ab ce ac bc abce Response values 63 21 36 99 24 66 71 54 Treatment Comb de ad bd abde cd acde bcde abcd Response values 23 74 80 33 63 21 44 96 (a) Identify the design, defining relation and the alias relationships (b) Estimate the main effects for factors (c) Suppose factors B and E are selected to be included in the model. Obtain an ANOVA table. (d) Estimate the regression coefficients for the fitted model (e) Comment on how to analyze residuals to check the model assumptions