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Duration
LevelApplied Multivariate Statistical Analysis (B-KUL-I0P16B)
Aims
Present the concepts and methods of multivariate analysis, emphasizing the applications and attempting to make the mathematics as palatable as possible.
The student is expected to:
- Apply linear algebra in variance, covariance and correlation structures and understand geometrical equivalents of basic multivariate reasoning
- Understand properties and applications of the Multivariate Normal distribution
- Carry out inference about multivariate means
- Understand and apply basic ordination, discrimination and classification methodologies: Principal Components Analysis, Factor Analysis, Discriminant Analysis and Cluster Analysis
- Be able to apply these methods on real datasets
- Make use of existing software packages to solve problems in Multivariate Analysis
Previous knowledge
Thorough knowledge of the basic concepts of statistics and their applications.
Prerequisites:
Applied statistical methods for bioinformatics (4 stp)
Linear algebra (6 stp)
Calculus (5 stp)
Exercises in Applied Mathematics and Statistics (3 stp)
Course material
Text book
Slides, transparencies, courseware
Examples and samples
Order of Enrolment
This course unit is a prerequisite for taking the following course units:
I0D47A : Linear and Generalised Linear Models
Is also included in other courses
- Doctoraatsopleiding in de Bio-ingenieurswetenschappen
- Master in de statistiek (Biometrics) 120 ects.
- Master in de bio-ingenieurswetenschappen: biosysteemtechniek (Major: Technology for the Agrifood Sector) 120 ects.
-
Master of Bioinformatics
120 ects.
-
Master of Tropical Natural Resources Management
120 ects.
-
Master in de bio-ingenieurswetenschappen: landbouwkunde
120 ects.
- Master in de bio-ingenieurswetenschappen: land- en bosbeheer (Major: Forestry and Nature Conservation) 120 ects.
- Master in de bio-ingenieurswetenschappen: land- en bosbeheer (Major: Production Forestry) 120 ects.
- Master in de bio-ingenieurswetenschappen: land- en bosbeheer (Major: Soil and Water) 120 ects.
-
Master in de bio-informatica
120 ects.
- Master of Earth Observation (Track 1: Bioscience Engineering) 120 ects.
- Master of Statistics (Biometrics) 120 ects.
Activities
4.0 ects. Applied Multivariate Statistical Analysis (B-KUL-I0P16a)
Content
Introduction: overview of different Multivariate Analysis methods
The Multivariate Normal distribution, sample geometry and random sampling.
The core of the course consists of two major parts:
1. Ordination methods or the analysis of covariance structures
- Principal Components Analysis, simple Correspondence Analysis
- Factor Analysis
- Canonical Correlation Analysis
2. Classification methods or the analysis of grouping structures
- Cluster Analysis
- Discriminant analysis, including Tree Based Models.
Description of learning activities
Ex cathedra, with emphasis on applications.
1.0 ects. Applied Multivariate Statistical Analysis: Practical Exercises (B-KUL-I0P17a)
Content
Introduction: overview of different Multivariate Analysis methods
The Multivariate Normal distribution, sample geometry and random sampling.
The core of the course consists of two major parts:
1. Ordination methods or the analysis of covariance structures
- Principal Components Analysis, simple Correspondence Analysis
- Factor Analysis
- Canonical Correlation Analysis
2. Classification methods or the analysis of grouping structures
- Cluster Analysis
- Discriminant analysis, including Tree Based Models
Description of learning activities
Ex cathedra, with emphasis on applications.
Evaluation
Evaluation : Applied Multivariate Statistical Analysis (B-KUL-I2P16b)
Explanation
Exercises on analysis of multivariate data.
Oral examination.
