What are the best practices and tools for validating and optimizing the models obtained from a CCD?
Central composite designs (CCDs) are a popular and efficient method for fitting response surface models to experimental data. They allow you to explore the effects of multiple factors and their interactions on a response variable, and to optimize the settings of the factors to achieve a desired outcome. However, to ensure the validity and robustness of your models, you need to follow some best practices and use some tools for validating and optimizing the models obtained from a CCD. In this article, you will learn about some of these practices and tools, and how they can help you improve your experimental design and analysis.