Design space refers to the multidimensional range of values for factors or variables that are considered during the design of experiments. It encompasses all possible combinations of input factors, allowing researchers to explore how changes in these factors affect responses or outcomes. Understanding design space is crucial in optimizing experimental conditions, especially in response surface methodology, optimal design theory, and specific designs like central composite and Box-Behnken designs.
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