29 Feb –
 18 Mar

Uppsala

PhD course - Multivariate methods for ecologists 3 (+1.5 optional) ECTS

The course aims to illustrate the application of number of multivariate methods on ecological data, as well as factors that should be considered in study design. Following the course, participants should be familiar with different multivariate techniques, and how they can be applied on various types of data. The course will focus on developing an understanding of the application of multivariate techniques, with only a minimum amount of effort placed on comprehending the underlying mathematical detail.

Course homepage

Contents:

A number of ordination and classification procedures will be demonstrated, such as table arrangement, cluster analysis, correspondence analysis (CA), canonical correspondence analysis (CCA), redundancy analysis (RDA), principle components analysis (PCA), partial least square-analysis (PLS) and more.

Time:

The course is given in two parts: The first part involves lectures and supervised computer exercises, and the second involves supervised individual work with own data at your own office. Course participants may register for either the first or both parts of the course.

Part 1: 1 week. 29 February-4 March 2016. At Ultuna campus.

Part 2: 2 weeks, directly after part 1, i.e., 7-18 March. At your own office except last day

Attendants:

The course is open for PhD students. We cannot accept undergraduate students.

Location:

The first part of the course will be given at the SLU campus, Uppsala. The second part of the course should be completed at your home department, with frequent contact with the teachers. The last day (18 March) is a compulsory assembly in Uppsala where the attendants present the results of the work during part 2.

Facts

Time: 2016-02-29 - 2016-03-18
Location: Uppsala
Last signup date: 31 January 2016
Additional info:

Software:

We will mainly use the commercial software CANOCO v.5. SLU affiliated students can have the program installed. Talk to the IT people at your department. Fon non-SLU students: a trial version can be requested from MicroComputer Power Opens in new window by sending a mail to Dr. Richard Furnas asking for a trial version to be used for this course.

We will also demonstrate how the programs R, PAST and Simca can be used for selected multivariate methods.

Computers:

We will do all exercises at a computer lab. You may bring your own laptop, provided that you have installed (at least) the trial version of CANOCO (see above).

Prerequisites:

Attendants must have basic experience in handling the Microsoft Windows operating system. A basic course in ordinary statistics is recommended. Students taking part 2 of the course must have own data to work with.

Teachers:

Ulf Grandin, David Angeler, Martyn Futter, Lars Sonesten

Course secretary:

Hannah Fried-Petersen  (mailto:hannah.fried.petersen@slu.se)

Credits:

Swedish PhD students will receive 3 ECTS credits for the first (lecture) part and 4.5 ECTS credits for completing the whole course.

Lodging:

There are several lodging alternatives in Uppsala. The hostel/hotel Sunnersta herrgård Opens in new window is located within walking distance from the SLU campus. In the city center, you can find many hotels and hostels (e,g, Uppsala City Hostel Opens in new window)

For more information contact:

Ulf Grandin (course content etc.), e-mail: ulf.grandin@slu.se

or

Hannah Fried-Petersen (application, practical matters, etc.), e-mail: mailto:hannah.fried.petersen@slu.se

Application:

Applications should be sent to Hannah Fried-Petersen.

The application should contain information on:

  • Name
  • Personnummer
  • Affiliation
  • Will take only Part 1 or the Full course

All students must also send a certificate that they are PhD students, mail adress will be provided in the mail confirming that we have recieved your application.

There are a limited number of places at the course. Attendants will be accepted in the order we recieve the applications, i.e. first come, first served! 

Last day for application is January 31, 2016.


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