Coursebooks 2017-2018

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Multivariate statistics with R in environment

ENV-521

Lecturer(s) :

Buttler Alexandre
Walker Thomas William Nicholas

Language:

English

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

Content

Keywords

Multivariable analysis, statistics for complexe data sets

Learning Prerequisites

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:

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

40 % spot written control (2h) during the semester
10 % continuous control (exercises) during the semester
50 % oral exam (30 min) during exam session

Supervision

Office hours Yes
Assistants Yes

Resources

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)

Ressources en bibliothèque
Notes/Handbook

Available on Moodle.epfl.ch

Websites
Moodle Link

Prerequisite for

Master project

In the programs

  • Environmental Sciences and Engineering, 2017-2018, Master semester 1
    • Semester
      Fall
    • Exam form
      Oral
    • Credits
      4
    • Subject examined
      Multivariate statistics with R in environment
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Environmental Sciences and Engineering, 2017-2018, Master semester 3
    • Semester
      Fall
    • Exam form
      Oral
    • Credits
      4
    • Subject examined
      Multivariate statistics with R in environment
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks
  • Mineur STAS Russie, 2017-2018, Autumn semester
    • Semester
      Fall
    • Exam form
      Oral
    • Credits
      4
    • Subject examined
      Multivariate statistics with R in environment
    • Lecture
      2 Hour(s) per week x 14 weeks
    • Exercises
      1 Hour(s) per week x 14 weeks

Reference week

MoTuWeThFr
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
Under construction
Lecture
Exercise, TP
Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German