ST808: Multivariate Data Analysis and Chemometrics

Study Board of Science

Teaching language: Danish or English depending on the teacher, but English if international students are enrolled
EKA: N370000102
Censorship: Second examiner: None
Grading: Pass/Fail
Offered in: Odense
Offered in: Autumn
Level: Master

STADS ID (UVA): N370000101
ECTS value: 5

Date of Approval: 25-04-2019


Duration: 1 semester

Version: Approved - active

Comment

15009501(former UVA) is identical with this course description. 

Entry requirements

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.

Content

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

See Blackboard for syllabus lists and additional literature references.

Examination regulations

Exam element a)

Timing

Autumn

Tests

Evaluation is based on three project reports regarding chemometric data analyses set during the course

EKA

N370000102

Censorship

Second examiner: None

Grading

Pass/Fail

Identification

Full name and SDU username

Language

Normally, the same as teaching language

Examination aids

To be announced during the course

ECTS value

5

Additional information

Reexam in the same exam period or immediately thereafter. The examination form for re-examination may be different from the exam form at the regular exam.

Indicative number of lessons

48 hours per semester

Teaching Method

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.

Teacher responsible

Name E-mail Department
Hans Christian Petersen hcpetersen@sdu.dk

Additional teachers

Name E-mail Department City
Nicky Cordua Mattsson mattsson@imada.sdu.dk

Timetable

44
Monday
26-10-2020
Tuesday
27-10-2020
Wednesday
28-10-2020
Thursday
29-10-2020
Friday
30-10-2020
08 - 09
09 - 10
10 - 11
11 - 12
12 - 13
Class f
Forelæsning
13 - 14
Class f
Forelæsning
14 - 15
Class f
Øvelser
15 - 16
Class f
Øvelser
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Administrative Unit

Institut for Matematik og Datalogi (datalogi, fiktiv)

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