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I'm a data scientist who has not used central composite design before, I only heard of it, but I'm not able to grasp for what it can be used and how it can be used.

Can someone please explain this to me in a high level for beginning and maybe point me to some useful literature?

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See http://www.itl.nist.gov/div898/handbook/pri/section3/pri3361.htm for instance. Central composite design consist of a factorial design or possible a fractional factorial design (see http://www.itl.nist.gov/div898/handbook/pri/section3/pri3331.htm) with one or more center points added. The purpose of adding center points is to be able ti fit quadratic terms to represent curvature, or simply to be able to check on linearity.

Such designs are useful in response surface modeling (see http://www.itl.nist.gov/div898/handbook/pri/section3/pri336.htm) and for surrogate models https://en.wikipedia.org/wiki/Surrogate_model

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