Objective:

This workshop introducing participants on how to interpret complex data quickly and confidently using most modem multivariate techniques. With a non-mathematical approach, participants can quickly and safety start using the methods in their own own to optimize, classify or predict products and processes.

Duration:

3 Full Days Workshop

Course Outline:

Design of Experiments

• What is Experimental Design
• Experimental Design in R&D Projects
• Screening Designs Optimization Designs and their Analysis
• Experimental design and PCA
• From Screening to Optimization
• Designs for product and process optimization
• Multivariate analysis of data collected on the basis of experimental designs

Multivariate Analysis

• The world is multivariate –Introduction to multivariate data modelling
• When are multivariate methods useful?
• Principal Component Analysis (PCA)
• Multivariate regression:
  • MLR- Multi Linear Regression
  • PCR- Principal Component Regression
  • PLS- Partial Least Squares
• Relevant data collection
• Multivariate modeling step by step
• Pretreatment and scaling
• Detecting and dealing with outliers
• Calibration, validation
• Prediction
• The different validation methods
• Basic rules for successful data analysis

Who Should Attend:

The courses have been designed for individuals:

• Involved in R&D, product development, process optimization, quality control & monitoring
• Working or likely to work with spectroscopic instruments (NIR, FTIR, UV, UV/VIS, NMR, Raman, Mass Spectroscopy),chromatography instruments (LC, GC) and other sources of multivariate data as part of laboratory, R&D, quality control or production processes