ANOVA Simultaneous Component Analysis (ASCA) is the current state-of-theart chemometric tool for analyzing and interpreting high-dimensional experimental data from a Design of Experiment (DoE). Being a multivariate extension of the ANOVA, ASCA makes a perfect tandem with DoE. This tutorial review recommends best practices for using ASCA, building upon the long-established combination of ANOVA and DoE theory developed over the last century. These recommendations are grounded in a comprehensive literature review and illustrated through a guiding example.

翻译：方差分析同步成分分析（ASCA）是目前分析实验设计（DoE）产生的高维实验数据并对其进行解释的前沿化学计量学工具。作为方差分析的多元扩展，ASCA与实验设计形成了完美的协同组合。本教程综述基于过去一个世纪以来已建立的ANOVA与DoE理论体系，推荐了使用ASCA的最佳实践。这些建议建立在对文献的全面综述基础之上，并通过典型案例进行阐述说明。