CAMO Software

Multivariate Data Analysis - Level 1

April 10-11, 2012 | Utrecht, Netherlands

Course Overview

For many years now, Multivariate Analysis (MVA) has been used by spectroscopists, analytical chemists, process engineers and sensory scientists to find important relationships in complex data tables. Methods such as Principal Component Analysis (PCA) have been used for data mining and exploratory data analysis purposes, while methods such as Partial Least Squares (PLS) have been used for predicting difficult to measure properties of products ranging from pharmaceuticals, petrochemical and agricultural comodities.

CAMO Software has been providing world recognized training courses in MVA for many years and this course on Advanced Multivariate Analysis builds on concepts introduced in other courses currently offered.

All course material will be supplemented with hands on practical exercises that highlight the use of each method discussed in a practical manner.

Prior experience with multivariate analysis or The Unscrambler®X is not required.

Who should participate in this program?

The courses have been designed for individuals:
  • Involved in R&D, product development, process optimization, quality control & monitoring
  • Working with complex data sets with many variables


If you want to study several variables at the same time and these are correlated, you need multivariate modeling strategies.

During the Multivariate Data Analysis – Level 1 workshop you will learn about:

  • The need for multivariate methods
  • Common applications
  • Importing and visualizing your data
  • Principal Component Analysis
  • Multiple Linear Regression
  • Principal Component Regression
  • Partial Least Squares Regression
  • Outlier detection
  • Validation of models

The workshop will contain both theory and practical usage of multivariate methods.

Course Details

Day 1
  • Section 1 — Introduction to Multivariate Analysis
    • The world is multivariate
    • Multivariate concepts
    • Multivariate examples
    • Data analysis workflow
  • Section 2 — Notions and terms used in MVA1
    • Explanatory, design and response variables
    • Dummy variables
  • Section 3 — Data import and handling
    • Historical data versus designed experiments
    • Importing and handling data
  • Section 4 — Diagnostics and plotting
    • Different plot types
    • Sample grouping
  • Lunch
  • Section 5 — Principal Component Analysis
    • Exploratory data analysis
    • The principle of projection
    • Interpretation
    • Background theory
    • Validation
    • Projection of new samples
Day 2
  • Section 6 — Outlier detection
    • What is an outlier
    • Different diagnostic plots
  • Section 7 — Regression methods
    • The concept
    • Multiple Linear Regression
    • Principal Component Regression
    • Partial Least Squares Regression
    • Interpretation
    • Prediction
  • Lunch
  • Section 8 — Validation methods
    • Why validate?
    • Modeling stages
    • Test set
    • Cross-validation
    • Replicates
    • What is the correct way to validate
  • Section 9 — How to be a good data analyst
    • Rules in multivariate analysis
    • Advice in modelling phase
    • Validity of models


Ir. Gerben Mooiweer Statistical Expert, Douwe Egberts/R&D

Gerben Mooiweer graduated from the Eindhoven University of Technology, Chemical Engineering and Chemistry department. He joined Douwe Egberts/R&D in 1977 as a technologist on coffee roasting, decaffeination, nut fryer temperature control, rice drying and various other projects focusing on mathematical modelling. In his current job he is a statistical expert for the Douwe Egberts R&D department. In this job he applies design of experiments, mathematical modelling and multivariate data analysis on a wide variety of data sources like sensory data, process data and metabolomics data using The Unscrambler® software. Beside his work at Douwe Egberts he is a guest lecturer at the TU Eindhoven teaching multivariate data analyses and MatLab courses.

General Terms

The course fees includes lunch, tea / coffee, course material and 30-days trial installation of The Unscrambler. Participants are required to bring their own Laptop, organize transport to / from training venue and accommodation at their own cost. Deadline for registrations: 2 weeks before the course start.

Payments: 30 days net from date of invoice.

Cancellation: Cancellations up to 1 week prior the course start date, will be refunded with 50% of the registration fee, after this limit will not be refunded.

Substitution: The course participants may be substituted or join a later training provided that CAMO is notified.


Industry: € 1250
Research: € 876
Academia: € 626


To be announced


Joseph McCurley
International Sales Manager
Phone: +47 22 39 63 00
Fax: +47 22 39 63 22