Exploratory Data Analysis / Chemometrics

Course content

In industry and research huge amounts of physical, chemical, sensory and other quality measurements are produced on all sorts of materials, processes and products. Exploratory data analysis / chemometrics offers a tool for extracting the optimal information from these data sets through the use of modern software and computer technology.
The course will give a step-by-step theoretical introduction to exploratory data analysis / chemometrics supported by practical examples from food science, environmental science, pharmaceutical science etc.
Methods for exploratory analysis (Principal Component Analysis), multivariate calibration (Partial Least Squares) and basic data preprocessing are considered. Understanding and interpretation of the computed models is central. As is methods for outlier detection and model validation. Computer exercises and cases will be performed applying user-friendly software. A thorough introduction to the software will be given.

Education

Bacheloruddannelsen i fødevarer og ernæring

Learning outcome

The course introduces basic chemometric methods (PCA and PLS) and their use on different kinds of multivariate data of relevance for research and development. Furthermore, the exploratory element in research and development is illustrated.

After completing the course the student should be able to:


Knowledge

  • Describe chemometric methods for multivariate data analysis (exploration and regression)
  • Describe techniques for data pre-preprocessing
  • Describe techniques for outlier detection
  • Describe method validation principles
  • Describe methods for variable selection
  • Understand the basics of the algorithms behind the PCA and PLS
  • Understand the math of data pre-processing

 

Skills

  • Apply theory on real life data analytical cases
  • Apply commercial software for data analysis
  • Interpret multivariate models (both exploratory and regression)

 

Competences

  • Discuss and respond to univariate versus multivariate data analytical methodology in problem solving in society

Lectures, cases and computer exercises will introduce the chemometric theory and the practical aspects of multivariate data analysis. During the course there will be four cases on real data analytical problems. The cases will mainly be based on data sets from research section Chemometrics & Analytical Technology, Department of Food Science.

See Absalon for a list of course literature

Competences in basic mathematics and statistics are recommended

Oral
Collective
Continuous feedback during the course of the semester
Peer feedback (Students give each other feedback)
ECTS
7,5 ECTS
Type of assessment
Oral examination, 15 min
Written assignment, during course
Individual oral examination without preparation time in the course curriculum. The oral examination weights 50%, while the remaining 50% is based on the final report. It is sufficient to pass the combined evaluation. However, omitting one of the two will be graded as a fail.
Aid
Only certain aids allowed

You are allowed to bring your written report to the exam

Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners
Criteria for exam assessment

See Learning Outcome

Single subject courses (day)

  • Category
  • Hours
  • Guidance
  • 7
  • Lectures
  • 24
  • Theory exercises
  • 35
  • Project work
  • 80
  • Preparation
  • 59
  • Exam
  • 1
  • English
  • 206