Multivariate statistics. Process systems engineering objectives: modeling, estimation, monitoring, control, optimization, and their relationship to data analytics. Feature extraction and dimension reduction, clustering, classification, regression. Nonlinear techniques and analysis of dynamic data. Applications of advanced data analytics in chemical process engineering.