





Self Running Tutorial 

Multivariate Data Analysis I 

Multivariate Data Analysis II 
Explore the self running tutorial with sample model files from The Unscrambler^{®}  30 day FREE trial version


 The world is multivariate  Introduction to multivariate data modeling
 When are multivariate methods useful?
 Principles and applications of PCA, MLR, PCR...


 Data preprocessing
 PCA
 Multivariate regression
 Prediction
 Classification (SIMCA and PLSDA)
 Multivariate Curve Resolution (MCR)






The Introducer 

Experimental Design (DoE) 

Multivariate Analysis Of
Spectroscopic Data 
Multivariate Data Analysis in Practice 5th Ed. by Prof. Kim Esbensen
 Practical applications of multivariate techniques such as PCA, PCR, and PLS
 Nonmathematical approach  ideal for analysts with little or no background in statistics
 Step by step introduction of new concepts and techniques that promotes ease of learning
 Theory supported by practical handson exercises based on realworld data


 Introduction to experimental design
 Questions experimental design can answer
 Classical experimental strategies / Why is experimental design useful?








Introduction to Chemometrics 

Multivariate Analysis of Sensory Data 

 Introduction: The world is multivariate
 Principal Component Analysis (PCA) – theory and applications
 Partial Least Squares Regression (PLSR) – ...


 Univariate statistics
 Experimental setup
 Evaluation of panel data
 Principal Component Analysis (PCA)
 Varimax rotation
 Preference mapping












Process modelling and optimisation 


 Design of experiments
 Efficient data collection
 Screening designs
 Optimization designs
 Evolutionary Operation (EVOP) design





