LLEF10174U Exploratory Data Analysis / Chemometrics
MSc Programme in Agriculture
MSc Programme in BIology- Biotechnology
The course will give a step-by-step theoretical introduction to exploratory data analysis / chemometrics supported by practical examples from food science, agro technology, medicine, pharmaceutical science etc.
Methods for exploratory analysis (Principal Component Analysis), multivariate calibration (Partial Least Squares) and basic data preprocessing are considered. Understanding and interpretation of the computed models is central. As is methods for outlier detection and model validation. Computer exercises and the project will be performed applying user-friendly software. A thorough introduction to the software will be given.
The course introduces basic chemometric methods (PCA and PLS) and their use on different kinds of multivariate data of relevance for research and development. Furthermore, the exploratory element in research and development is illustrated.
After completing the course the student should be able to:
Describe chemometric methods for multivariate data analysis (exploration and regression)
Describe techniques for data pre-preprocessing
Describe techniques for outlier detection
Describe method validation principles
Describe methods for variable selection
Apply theory on real life data analytical cases
Apply commercial software for data analysis
Report in writing a full data analysis of a given problem including all aspects presented under Knowledge.
Interpret multivariate models (both exploratory and regression)
Discuss and respond to univariate versus multivariate data analytical methodology in problem solving in society
Notes, papers and other course material.
- Project work
- Theory exercises
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- 7,5 ECTS
- Type of assessment
- Oral examination, 15 minutes under invigilation---
- Exam registration requirements
- Handing in written report
- Only certain aids allowed
You're allowed to bring your written report to the exam
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
There will be one internal censor for the exam.