Chemometrics

2019/2020

Content, progress and pedagogy of the module

Learning objectives

Knowledge

Students who have passed the module should be able to

  • Account for general methods for multivariate data analysis (principal component analysis, multiple linear regression, principal component regression, projection on latent structures, soft independent modelling of class analogy)
  • Account for methods for data preprocessing (centering, scaling, non-linear and spectroscopic preprocessing, orthogonal signal correction)
  • Explain basic methods for variable selection (Selectivity ratio, VIP, interval PLS, jack-knife)
  • Explain the theoretical background of these methods, their advantages and limitations as well as possible applications
  • Explain how multivariate methods complement traditional statistical methods

Skills

  • Explore multivariate data, find groups and trends, detect and remove outliers
  • Calibrate and do proper validation of multivariate regression models, use these models for prediction
  • Evaluate if data need a preprocessing and which method to apply
  • Calibrate and evaluate models for data classification
  • Compare different regression and classification models and find which is the best
  • Use multivariate methods for analysis of real data from different applications

Type of instruction

  • Lectures, classroom instruction and mini-projects

Extent and expected workload

150 hours

Exam

Exams

Name of examChemometrics
Type of exam
Written exam
ECTS5
AssessmentPassed/Not Passed
Type of gradingInternal examination
Criteria of assessmentAs stated in the Joint Programme Regulations

Facts about the module

Danish titleKemometri
Module codeK-KT-K1-9
Module typeCourse
Duration1 semester
SemesterAutumn
ECTS5
Language of instructionEnglish
Empty-place SchemeYes
Location of the lectureCampus Esbjerg
Responsible for the module

Organisation

Study BoardStudy Board of Biotechnology, Chemistry and Environmental Engineering
DepartmentDepartment of Chemistry and Bioscience
FacultyFaculty of Engineering and Science