Frequently Asked Questions Raman Multivariate Analysis HORIBA Training

Multivariate analysis in Raman spectroscopy involves using statistical and chemometric methods to process, interpret and extract meaningful information from complex Raman datasets. It helps identify spectral patterns, classify samples and investigate relationships between different chemical components.

This course is intended for HORIBA Raman spectrometer users who already understand Raman spectroscopy fundamentals and have experience using HORIBA Raman systems and LabSpec software.

Yes. Participants should already understand Raman spectroscopy fundamentals and know how to operate their HORIBA Raman system. Attending the RAM1 basic Raman training beforehand is recommended.

The training introduces several multivariate analysis methods, including Principal Component Analysis (PCA), Multivariate Curve Resolution (MCR), Partial Least Squares (PLS), Classical Least Squares (CLS), Hierarchical Cluster Analysis (HCA) and K-means clustering.

The course lasts one day and combines theoretical presentations with practical exercises using demonstration and customer datasets.

Yes. Participants receive a training certificate upon completion of the course.

Yes. We also offers personalized training programs adapted to your instrument, applications and learning objectives. Contact HORIBA France to discuss your requirements.