Multivariate Data Analysis - I
The world is multivariate - Introduction to multivariate data modeling
- When are multivariate methods useful?
- Principles and applications of:
- Principal Component Analysis (PCA)
- Multivariate regression: Multilinear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS)
- Relevant data collection
- Multivariate modeling step by step
- Pretreatment and scaling
- Detecting and dealing with outliers
- Calibration, validation
- The different validation methods
- Basic rules for successful data analysis
Who should participate in this program?
The courses have been designed for individuals:
- Involved in consumer insights, R&D, product development, process optimization, quality
control & monitoring.
- Working with spectroscopic instruments (NIR, FTIR, UV, UV/VIS, NMR, DAS, Raman, Mass
Spectroscopy) chromatography instruments (LC, CE, GC, HPLC), production data & sensory
data, R&D, quality control or production processes.
No prior knowledge of The Unscrambler® is required to attend our courses.
- The number of seats for the course is limited to 12
- Deadline for registrations: 3 weeks before the course-start
- Participants are required to bring their own Laptop.
Find a MVA - Level I training course near you