Chemometrics and Process Monitoring


Content, progress and pedagogy of the module

Learning objectives


Students who complete the module must 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, nonlinear and spectroscopic reprocessing, 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


  • 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 identify the best
  • use multivariate methods for analysis of real data from different applications

Type of instruction

  • Lectures
  • Workshops
  • Exercises
  • Mini-projects

Extent and expected workload

150 hours



Name of examChemometrics and Process Monitoring
Type of exam
Written or oral exam
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleKemometri og procesovervågning
Module codeK-KT-K2-36
Module typeCourse
Duration1 semester
Language of instructionEnglish
Empty-place SchemeYes
Location of the lectureCampus Esbjerg
Responsible for the module


Study BoardStudy Board of Chemistry and Bioscience
DepartmentDepartment of Chemistry and Bioscience
FacultyThe Faculty of Engineering and Science