PFS0163 Multivariate statistics, 4.0 Credits
Subjects Mathematic Statistics
No Level Indicated
Pass / Failed
The requirements for attaining different grades are described in the course assessment criteria which are contained in a supplement to the course syllabus. Current information on assessment criteria shall be made available at the start of the course.
A basic course in univariate statistics. The Multivariate Statistics course will be taught using matrix notation and assuming some knowledge of matrix algebra. The absence of training in matrix algebra should not, however, form an obstacle to taking the course so long as you are prepared to put in some additional work early on learning a few, key matrix operations
The course is primarily intended for graduate students, but post-doctoral researchers are also welcome to attend.
Upon successful completion of the course participants will be able to analyze data visually, using exploratory data analysis, as well as statistically, using multivariate statistical tools, and also to critically examine the validity of the statistical analyses.
• Principal components analysis
• Multivariate normality
• Cluster analysis
• Discriminant analysis
• Multi dimensional Scaling
• Factor analysis
• Canonical correlation analysis
Formats and requirements for examination
The participant will receive 4.0 credits upon successful completion of a home examination.
The course can accommodate a limited number of applicants, who will be accepted in the order which the organizer receives the applications.
Applications are to be sent by e-mail to Magnus Ekström (email@example.com) and should contain the following information.
• Name of the course;
• Name of applicant;
• Personal identification number (personnummer);
• Academic affiliation;
• Graduate student or Post-doc.
Department of Forest Resource Management