This presentation, prepared for Materials Technology@TMS, gives a brief description of the mathematical basis for Principal Component Analysis, an approach that allows for identifying patterns in large data sets. It then highlights a case study of the application of the method to molten salts, referring to the following publication: Gadzuric, S., Suh, C., Gaune-Escard, M., Rajan, K., "Dimensionality Reduction: Case Study, Extracting Information from the Molten Salt Database," Metallurgical and Materials Transactions, 37A, December 2006.

CITATION: C. Suh, S. Graduciz, M. Gaune-Escard, K. Rajan, "Data Dimensionality Reduction: Introduction to Principal Component Analysis, Case Study: Multivariate Analysis of Chemistry-Property Data in Molten Salts", Materials Technology@TMS, 2007.