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A central composite design is run for analysis of a chemical process, resulting

ID: 3294715 • Letter: A

Question

A central composite design is run for analysis of a chemical process, resulting in the experimental data shown in the MINITAB Analysis Packet. The objective of the analysis was to identify settings that would maximize process discharge. Refer to the packet and answer the following questions: Is the regression significant? Explain. (Can you comment about any assumptions?); Compute the R2 and compare to the result provided by Minitab. Comment on the quality of the regression based on the magnitude of the R2 value. Based on your review of the Minitab output write out the regression model for this experiment. What is the approximate best setting to maximize the process discharge?
SET UP the calculations for the stationary point.

Analysis Results for Process Discharge S = 0.2660 R-Sq = 98.3% R-Sq (adj) = 97.0% PRESS = 2.34577 R-Sq (pred)= 91.84%

Explanation / Answer

a) H0: The regression is not significant
H1: The regression is significant
Let the los be alpha = 5%
From the output, P-value of regression is 0.000 < alpha 0.05, so we reject H0
Thus, we conclude that the regression is significant
b)
R-square = 98.3% percentage of variation in the dependent variable is explained by the independent variables
c)
The multiple regression of Process Discharge is
Process Discharge is = 79.94 + 0.9950A + 0.5152B - 1.3762A2 - 1.0013B2 + 0.25AB

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