ENV-521 / 4 crédits

Enseignant:

Langue: Anglais

Remark: pas donné en 2021-22

## Summary

Introduction to multivariate data analysis and modelling. The course helps for a critical choice of methods and their integration in a research planning. It prepares for complexe data analysis in various fields of environemental sciences. Use of dedicated R libraries

## Keywords

Multivariable analysis, statistics for complexe data sets

## Recommended courses

Probabilities and statistics

Experimental Design and Data Analysis with R" (EDDAR - ENG 467)

## Learning Outcomes

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

• Select appropriately methods for data analysis knowing the basic principles of calculation in the field of their application
• Construct a plan for data analysis
• Interpret properly the results given by the different methods
• Apply the methods with exercices and a personal project
• Work out / Determine means for combining data from two or more independant data sets describing the same objects and test the relationship

## Teaching methods

Lecture and exercises on computer, personel project for applying methods.

## Expected student activities

Participating at the lecture and reading the hand-out

Applying the various methods with the exercices and provided data set

Personal project with report and defense

## Assessment methods

50 % project report during the semester
50 % oral exam (30 min) during exam session on the personal project

## Supervision

 Office hours Yes Assistants Yes

## Bibliography

BIBLIOGRAPHY

Legendre, P., & Legendre, L. (2012) Numerical Ecology. 3e ed., Elsevier ***

Jongman, R.H.G, Ter Braak, C.J.F. & Van Tongeren, O.F.R. (1987) Data analysis in community and landscape ecology. PUDOC, Wageningen

Borcard, D., Gillet, F. & Legendre, P. (2011) Numerical Ecology with R. Springer Verlag.*

*** for theory and fundamental concepts

* to work with R (codes)

## Notes/Handbook

Available on Moodle.epfl.ch

Master project

## Dans les plans d'études

• Semestre: Automne
• Forme de l'examen: Oral (session d'hiver)
• Matière examinée: Statistiques multivariables avec R
• Cours: 2 Heure(s) hebdo x 14 semaines
• Exercices: 1 Heure(s) hebdo x 14 semaines
• Semestre: Automne
• Forme de l'examen: Oral (session d'hiver)
• Matière examinée: Statistiques multivariables avec R
• Cours: 2 Heure(s) hebdo x 14 semaines
• Exercices: 1 Heure(s) hebdo x 14 semaines
• Forme de l'examen: Oral (session d'hiver)
• Matière examinée: Statistiques multivariables avec R
• Cours: 2 Heure(s) hebdo x 14 semaines
• Exercices: 1 Heure(s) hebdo x 14 semaines

## Semaine de référence

 Lu Ma Me Je Ve 8-9 9-10 10-11 11-12 12-13 13-14 14-15 15-16 16-17 17-18 18-19 19-20 20-21 21-22