Anova Simultaneous Component Analysis (ASCA) is a versatile tool for analyzing multivariate data from designed experiments. Based on anova variance partitioning followed by bi-linear modelling of the individual effect matrices the method offers detailed insight into small systematic variance contributors that otherwise are masked and uncovered by traditional techniques such as PCA. This workshop will uncover the basic principals in ASCA and give the attendees hands-on experience on how to use the tool on real data using the PLS-toolbox® in Matlab®.

Lecturer: Post. Doc. Morten Arendt Rasmussen (University of Copenhagen)

Price: € 300 / 400 (academic / industry)

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