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Multivariate Data Analysis
Provider: Faculty of Science

Activity no.: 5336-25-00-00There are 45 available seats 
Enrollment deadline: 02/11/2025
PlaceDepartment of Food Science
Date and time01.12.2025, at: 09:00 - 05.12.2025, at: 16:00
Regular seats45
Activity Prices:
  - 1 Participant fee (all participants in add. to course fee)0.00 kr.
  - 2 Course fee PhD student enrolled at UCPH SCIENCE0.00 kr.
  - 3 Course fee PhD student at Danish Universities (except CBS)0.00 kr.
  - 4 Course fee PhD student at Copenhagen Business School3,000.00 kr.
  - 5 Course fee PhD student at foreign university3,000.00 kr.
  - 6 Course fee Master's student at Danish university0.00 kr.
  - 7 Course fee Master's student at foreign university3,000.00 kr.
  - 8 Course fee Employee at university (e.g., postdocs)3,000.00 kr.
  - 9 Course fee Others (e.g., from a private company)8,400.00 kr.
LecturersÅsmund Rinnan
ECTS credits2.50
Contact personÅsmund Rinnan    E-mail address: aar@food.ku.dk
Enrolment Handling/Course OrganiserPhD Administration SCIENCE    E-mail address: phdcourses@science.ku.dk
Enrolment guidelines
This is a toolbox course where 80% of the seats are reserved to PhD students enrolled at the Faculty of SCIENCE at UCPH and 20% og the seats are reserved to PhD students from other Danish Universities/faculties (except CBS).

Anyone can apply for the course, but if you are not a PhD student at a Danish university (except CBS), you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to applicants on the waiting list.

The course is free of charge for PhD students at Danish universities (except CBS).

All other participants must pay the course fee (except if you are a master’s student from a Danish University).


Aim and 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 digitalization (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. The mathematics behind most of the concepts will be given together with the practical applications and considerations of the methods.
Even more important, though, is the understanding and interpretation of the computed models. 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.
Course content:
• Introduction to Multivariate Data Analysis
• Principal Component Analysis (PCA)
• Pre-processing
• Outlier detection
• Partial Least Squares Regression (PLSR)
• Validation
• Variable selection


Learning outcomes
Intended learning outcome for the students who complete the course:

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
• 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


Target Group
PhD students from any scientific field that gather data with several samples (+10) and many variables (+10)


Recommended Academic Qualifications
Basic statistical knowledge.


Research Area
Any that collect larger amounts of data, i.e. environmental sciences, chemistry, food, pharma and biology


Teaching and Learning Methods
There will be a mixture of several different teaching methodologies:
- Lectures (most also available as videos)
- Exercises + Walkthrough
- Short cases + Fish tank
- Day cases + Debriefing sessions
- Visual examples


Type of Assessment
A short report of three pages with data analysis on own/ provided data to be handed in and approved. This report may be written in groups of two.


Literature
- Bro R, Smilde AK (2014): Principal component analysis, Analytical Methods, 6, 2812
- Geladi P, Kowalski BR (1986): Partial Least Squares Regression – A tutorial, Analytical Chimica Acta, 185, 1-17
- Rinnan Å, van den Berg F, Engelsen SB (2009): Review of the most common pre-processing techniques for near-infrared spectra, Trends in Analytical Chemistry, 28 (10), 1201-1222
- Andersen CM, Bro R (2010): Variable selection in regression – A tutorial, Journal of Chemometrics, 24, 728-737
- Kjeldahl K, Bro R (2010): Some common misunderstandings in chemometrics, Journal of Chemometrics, 24, 558-564
- A series of short articles in Spectroscopy Europe named the Tony Davies Column


Course coordinator
Åsmund Rinnan, Associate Professor, aar@food.ku.dk


Dates
December 1-5, 2025


Course location
Frederiksberg Campus


Registration

Requirements for signing up
No requirements


Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the deadline for registration.




Cancellation policy
• Cancellations made up to two weeks before the course starts are free of charge.
• Cancellations made less than two weeks before the course starts will be charged a fee of DKK 3.000
• Participants with less than 80% attendance cannot pass the course and will be charged a fee of DKK 5.000
• No-show will result in a fee of DKK 5.000
• Participants who fail to hand in any mandatory exams or assignments cannot pass the course and will be charged a fee of DKK 5.000

Course fee and participant fee
PhD courses offered at the Faculty of SCIENCE have course fees corresponding to different participant types.
In addition to the course fee, there might also be a participant fee.
If the course has a participant fee, this will apply to all participants regardless of participant
type - and in addition to the course fee.

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