Interaction in a Two-Factor Regression Model

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This Demonstration considers the effect of interaction in a two-factor factorial experiment.

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A regression model representation of a two-factor factorial experiment can be written as

,

where represents the response, factor 1, factor 2, the s are parameters with values to be determined and is a random error term.

If you increase the value of the interaction coefficient , the twisting of the response surface increases [1]. This is most apparent in the curvature of the contour lines in the 3D and contour plots.

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Contributed by: R. Ricardo Sánchez (May 2021)
Open content licensed under CC BY-NC-SA


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Reference

[1] D. C. Montgomery, Design and Analysis of Experiments, 9th ed., Hoboken, NJ: John Wiley & Sons, 2017.



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