Methods in data analysis
By our definition of multivariate technology, there are two basic approaches:
Design of Experiments and Multivariate Data Analysis.
Multivariate Data Analysis (MVDA)
extracts the information from large data sets and presents the results as interpretable plots based on the mathematical principle of projection. Even data characterised by thousands of variables can be reduced to just a few information rich plots. Understanding the results in terms of the original measured variables is only ever a mouse click away.
Design of Experiments (DOE)
is the most efficient way of selecting a diverse and representative set of experiments when a process or system involves two or more variables. The approach is highly efficient in terms of the number of experiments per variable investigated. The results include a predictive model, which may be explored to find the optimal operating conditions.