Course syllabus

Kemometri - försöksplanering och multivariat analys
Chemometrics - Design of Experiments and Multivariate Analysis

KLGN10, 7,5 credits, A (Second Cycle)

Valid for: 2020/21
Decided by: PLED B/K
Date of Decision: 2020-03-27

General Information

Elective for: B5-l, B5-mb, B5-lm, K5-m, K5-l, N4
Language of instruction: The course will be given in English on demand

Aim

Build on the knowledge in design of experiments in order to be able to plan and perform more complicated experiments, as well as analyse data in several dimensions.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

• be able to explain and use basic methods in factorial design,
• be able to explain and use basic methods in cluster analysis, discriminant analysis, principal components, and partial least squares.

Competences and skills
For a passing grade the student must

• plan a factorial design experiment,
• suggest which multivariate statistical method should be used on a given problem,
• structure and analyse multi-dimensional data materials using computer software for multivariate methods, and critically assess the result,
• report the solutions of multivariate statistical problems in written reports and orally at seminars.

Contents

Complete and reduced factorial designs. Response surface analysis. Cluster analysis, discriminant analysis, principal component analysis (PCA), and partial least squares (PLS).

Examination details

Grading scale: TH - (U,3,4,5) - (Fail, Three, Four, Five)
Assessment: Written project reports as well as compulsory and active participation in the seminars.

The examiner, in consultation with Disability Support Services, may deviate from the regular form of examination in order to provide a permanently disabled student with a form of examination equivalent to that of a student without a disability.

Admission

Admission requirements:

• FMA420 Linear Algebra or FMA421 Linear Algebra with Scientific Computation or FMA656 Mathematics, Linear Algebra or FMAA20 Linear Algebra with Introduction to Computer Tools or FMAB20 Linear Algebra

Assumed prior knowledge: A basic course in mathematical statistics and basic MATLAB programming.
The number of participants is limited to: No
The course overlaps following course/s: FMS210

Reading list

• Brereton, RG: Chemometrics, Data driven extraction for science. Wiley, 2018.

Contact and other information

Teacher: Malin Sjöö, malin.sjoo@food.lth.se
Course coordinator: Andreas Håkansson, andreas.hakansson@food.lth.se
Course homepage: http://www.food.lth.se/english/education/