Central composite design: Difference between revisions

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{{Short description|Experimental design in statistical mathematics}}

In [[statistics]], a '''central composite design''' is an experimental design, useful in [[response surface methodology]], for building a second order (quadratic) model for the [[response variable]] without needing to use a complete three-level [[factorial experiment]].

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=== Application of central composite designs for optimization ===

Statistical approaches such as RSM[[Response Surface Methodology]] can be employed to maximize the production of a special substance by optimization of operational factors. In contrast to conventional methods, the interaction among process variables can be determined by statistical techniques. For instance, in a study, a central composite design was employed to investigate the effect of critical parameters of organosolv pretreatment of rice straw including temperature, time, and ethanol concentration. The residual solid, lignin recovery, and hydrogen yield were selected as the response variables.<ref name="Organosolv">{{cite journal|last1=Asadi|first1=Nooshin|last2=Zilouei|first2=Hamid|title=Optimization of organosolv pretreatment of rice straw for enhanced biohydrogen production using Enterobacter aerogenes|journal=Bioresource Technology|date=March 2017|volume=227|pages=335–344|doi=10.1016/j.biortech.2016.12.073|url=https://www.researchgate.net/publication/311881656_Optimization_of_organosolv_pretreatment_of_rice_straw_for_enhanced_biohydrogen_production_using_Enterobacter_aerogenes311881656|pmid=28042989|bibcode=2017BiTec.227..335A }}</ref>

==References==