ENV-513 / 4 credits

Teacher: Peter Hannes Markus

Language: English

## Summary

Data required for ecosystem assessment is typically multidimensional. Multivariate statistical tools allow us to summarize and model multiple ecological parameters. This course provides a conceptual introduction and guidelines for the use of multivariate statistical tools using the R platform.

## Content

1. Biological and environmental data, multidimensional data, and the R platform
2. Resemblance, similarity and dependence measures
3. Unsupervised and supervised clustering techniques
4. Ordination techniques (PCA, CA, PCoA, NMDS)
5. Constrained ordination (RDA, CCA, db-RDA)
6. Statistical tests for multivariable responses (anosim, betadisper)

## Keywords

Multivariable analysis, statistics for ecological data sets, ordination, clustering

## Learning Outcomes

By the end of the course, the student must be able to:

• Explore multivariate datasets
• Select appropriately the methods for multivariate data analysis
• Explain the basic principles of various tools
• Interpret obtained results
• Apply methods in exercices and in a personal project

## Transversal skills

• Communicate effectively with professionals from other disciplines.

## Teaching methods

Lectures and computer exercises. Personal projects.

## Expected student activities

• Active participation in lectures and excercises.
• Application of methods to example and a personal dataset
• Presentation of results (oral and written)

## Assessment methods

• active participation (20%)
• oral presentation (30%)
• written exam (50%)

## Supervision

 Office hours Yes Assistants Yes Forum Yes Others moodle

## In the programs

• Semester: Fall
• Exam form: Written (winter session)
• Subject examined: Multivariate statistics in R
• Lecture: 2 Hour(s) per week x 14 weeks
• Exercises: 1 Hour(s) per week x 14 weeks
• Type: optional
• Semester: Fall
• Exam form: Written (winter session)
• Subject examined: Multivariate statistics in R
• Lecture: 2 Hour(s) per week x 14 weeks
• Exercises: 1 Hour(s) per week x 14 weeks
• Type: optional
• Exam form: Written (winter session)
• Subject examined: Multivariate statistics in R
• Lecture: 2 Hour(s) per week x 14 weeks
• Exercises: 1 Hour(s) per week x 14 weeks
• Type: optional

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