Multivariate Statistical Methods, 6 credits
Multivariata Statistiska Metoder, 6 hp
732A37
Main field of study
StatisticsCourse level
Second cycleCourse type
Single subject and programme courseDirector of studies or equivalent
Lotta HallbergCourse offered for | Semester | Weeks | Language | Campus | ECV | |
---|---|---|---|---|---|---|
F7MSG | Master´s Programme in Statistics and Data Mining | 1 (Autumn 2016) | 201643-201651 | English | Linköping | E |
Main field of study
StatisticsCourse level
Second cycleAdvancement level
A1XCourse offered for
- Master´s Programme in Statistics and Data Mining
Entry requirements
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.
Intended learning outcomes
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
Course content
- training in matrix algebra
- multivariate normal distribution and inference of mean vectors
- principal component analysis and factor analysis
- canonical correlation analysis
- multidimensional scaling
Teaching and working methods
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.
Examination
Reports on computer assignments. A final oral or written examination.
Grades
ECTS, ECOther information
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.
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.
Department
Institutionen för datavetenskapNo examination details is to be found.
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