ST808: Multivariate Data Analysis and Chemometrics (5 ECTS)

STADS: 15009501

Level
Master's level course approved as PhD course

Teaching period
The course is offered in the autumn semester.

Teacher responsible
Email: hcpetersen@imada.sdu.dk

Timetable
Show entire timetable
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Comment:
Ubegrænset deltagerantal

Prerequisites:
None.

Academic preconditions:
Students taking the course are expected to have knowledge of linear algebra and basic statistics.

Course introduction
The aim of the course is to enable the student to study multivariate calibration techniques and their applications in chemometrics.

The course builds on the knowledge acquired in the courses linear algebra and mathematical statistics.

In relation to the competence profile of the degree it is the explicit focus of the course to:

• Give the competence to plan and execute scientific projects at a high level, including the management of work and development situations that are complex, unpredictable and that require new problem solving skills
• Give skills to master computer calculations
• Give knowledge about advanced models and methods in applied mathematics, based on international research, and knowledge about application of these models and methods on problems from various disciplines and from the private sector.

Expected learning outcome
The learning objectives of the course are that the student demonstrates the ability to:

• describe the main chemometric methods for multivariate calibration and to know how to apply these in a specific context.
• know the application of a statistical software package, such as R, for solving concrete multivariate calibration problems, and to be able to describe the result of such an analysis in the form of a report.
• describe the advantages and disadvantages of different chemometric methods, in order to choose the correct method to solve a given multivariate calibration problem.
• describe the main methods for validation and optimization of a given calibration method for a specific problem, in order to assess the correctness of the method in the given context.

Subject overview
The following main topics are contained in the course:

• Repetition of basic concepts from statistics and matrix algebra.
• Introduction to chemometrics and multivariate calibration.
• Multiple linear regression analysis (MLR).
• The classical least squares method (CLS).
• Principal components analysis (PCA).
• Principal components regression (PCR).
• Partial least squares regression (PLS).
• Validation and optimization of calibration model.

Literature

Meddeles ved kursets start.

Website
This course uses e-learn (blackboard).

Prerequisites for participating in the exam
None

Assessment and marking:
Evaluation is based on three project reports regarding chemometric data analyses set during the course. Pass/fail, internal marking by the teacher.

Reexam in the same exam period or immediately thereafter. The evaluation form can be different for reexam.

Expected working hours
The teaching method is based on three phase model.
Intro phase: 24 hours
Skills training phase: 24 hours, hereof:
 - Laboratory exercises: 24 hours

Educational activities

Educational form
Activities during the study phase: To study the course material and familiarise oneself with the statistical analyses in the R software package, individually or through group work.

Language
This course is taught in Danish or English, depending on the lecturer. However, if international students participate, the teaching language will always be English.

Course enrollment
See deadline of enrolment.

Tuition fees for single courses
See fees for single courses.