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Latent Variable Methods for Engineering: CHE 765

Administrative Course outline Location and hours Course videos Copyright and other legal stuff Announcements Course videos are now available Preparation for next class -- get ready for some math: we're going in-depth to understand exactly what \( \mathbf{T = XP} \) means Link to software download (version 11.08) Review on your own the last section of the slides on data visualization

Class materials 1: Course overview and introduction to latent variable methods 2,3: Principal component analysis (PCA) 4: Application of PCA to process monitoring 5: Projection to latent structures (PLS) 6,7,8 Applications of latent variable methods 9,10 Dealing with 3D data: batch and image data 11 Multiblock data analysis: dealing with data from multiple sources 12 Optimization and new product development 13 Course project presentations Review of basic statistical concepts References and readings

Assignments, projects and datasets Assignments Assignment 1 Assignment 2 Assignment 3 Assignment 4 Project Course project description All course datasets

Course calendar