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Multivariate Statistical Methods, 6 ECTS Credits
COURSE CATEGORY   Master´s Programme in Statistics and Data Mining
  COURSE CODE   732A37
After completion of the course, the student should be able to:
- use multivariate inference methods generalizing widely used univariate methods
- demonstrate insightful understanding of covariance structures in the analysis of multivariate data
- select and apply suitable methods for extracting, summarizing and analyzing the information carried by multivariate data
- training in matrix algebra
- multivariate normal distribution and inference of mean vectors
- principal component analysis and factor analysis
- canonical correlation analysis
- multidimensional scaling
The teaching comprises lectures, seminars, and computer exercises. Lectures are devoted to presentations of theories, concepts and methods. Computer exercises provide practical experience of analyzing multivariate data. The seminars comprise student presentations and discussions of computer assignments.
Language of instruction: English.
Reports on computer assignments. A final oral or written examination.

Students failing an exam covering either the entire course or part of the course two times are entitled to have a new examiner appointed for the reexamination.

Students who have passed an examination may not retake it in order to improve their grades.

For acceptance to the course, the student must have a bachelor’s degree with a total of at least 90 ECTS credits (1.5 years of full-time studies) in mathematics, applied mathematics, statistics, and computer science. The undergraduate courses in mathematics should include both calculus and linear algebra. Basic undergraduate course in computer science and at least one intermediate course in each of the following areas: probability theory, statistical inference and linear statistical models are also required.
Documented knowledge of English equivalent to Engelska B/Engelska 6 internationally recognized test, e.g. TOEFL (minimum scores: Paper based 575 + TWE-score 4.5, and internet based 90), IELTS, academic (minimum score Overall band 6.5 and no band under 5.5), or equivalent.
The course is graded according to the ECTS grading scale A-F
Course certificate is issued by the Faculty Board on request. The Department provides a special form which should be submitted to the Student Affairs Division.
The course literature is decided upon by the department in question.
Planning and implementation of a course must take its starting point in the wording of the syllabus. The course evaluation included in each course must therefore take up the question how well the course agrees with the syllabus.

The course is carried out in such a way that both men´s and women´s experience and knowledge is made visible and developed.
Multivariate Statistical Methods
Multivariata Statistiska Metoder
Department responsible
for the course or equivalent:
IDA - Department of Computer and Information
Registrar No: 1330/06-41   Course Code: 732A37      
    Exam codes: see Local Computer System      
Subject/Subject Area : Statistik - STA          
Level   Education level     Subject Area Code   Field of Education  
A1X   Advanced level     STA   SA  
The syllabus was approved by the Board of Faculty of Arts and Science 2008-09-10
Latest revision 2013-03-18