Question: The article Experimental Design Approach for the Optimization of the Separation of Enantiomers in Preparative Liquid Chromatography (S. Lai and Z. Lin, Separation Science and

The article €œExperimental Design Approach for the Optimization of the Separation of Enantiomers in Preparative Liquid Chromatography€ (S. Lai and Z. Lin, Separation Science and Technology, 2002: 847€“875) describes an experiment involving a chemical process designed to separate enantiomers. A model was fit to estimate the cycle time (y) in terms of the flow rate (x1), sample concentration (x2), and mobile-phase composition (x3). The results of a least-squares fit are presented in the following table. (The article did not provide the value of the t statistic for the constant term.)

Predictor Coefficient Constant 1.603 X1 -0.619 -22.289 0.000 X2 0.086 3.084 0.018

Of the following, which is the best next step in the analysis?

i. Nothing needs to be done. This model is fine. 

ii. Drop x21 , x22 , and x23 from the model, and then perform an F test.

iii. Drop x1x2, x1x3, and x2x3 from the model, and then perform an F test.

iv. Drop x1 and x21 from the model, and then perform an F test.

v. Add cubic terms x31 , x32 , and x33 to the model to try to improve the fit.

Predictor Coefficient Constant 1.603 X1 -0.619 -22.289 0.000 X2 0.086 3.084 0.018 X3 0.306 11.011 0.000 0.272 8.542 0.000 0.057 1.802 0.115 0.105 3.300 0.013 X1X2 -0.022 -0.630 0.549 X1X3 -0.036 -1.004 0.349 X2X3 0.036 1.018 0.343

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