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Course Catalog 2011-2012
MAT-41286 Multivariate Statistical Methods, 6 cr |
Additional information
This is a self-study course.
Suitable for postgraduate studies
Person responsible
Keijo Ruohonen
Lessons
Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
Closed-book written exam.
Completion parts must belong to the same implementation
Learning outcomes
After completing the course the student is able to choose, apply and analyze the results of common multivariate statistical methods. Since the course is mainly a self-study course, the student may choose the material to emphasize application areas of specific interest. The student will also be familiar with the multivariate modelling tools in a statistical program (MATLAB, JMP, R or some such). Nowadays these methods form a long-standing well-researched and much used, and therefore it is simply not possible to include outcomes for them all within a single course. Completing the course the student nevertheless should be able the generalize and extend the skills.
Content
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Multivariate probability calculus, in particular the multinormal distribution. | ||
2. | Regression modelling. ANOVA. | ||
3. | Principal component analysis. Clustering, and other standard multivariate methods. |
Evaluation criteria for the course
Final grade is determined from a closed-book exam. Passing the course requires passing the final exam, and for this at most half of the maximum points are required. Mastering basic methods of the core content should be sufficient for passing the course with grade 3. To get the degree 4 a more thorough mastering is required, getting the grade 5 then requires skills of using this knowledge in new modelling situations.
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Partial passing:
Study material
Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
Book | Applied Multivariate Data Analysis | Everitt, B.S. & Dunn, G. | 0470711175 | English | |||
Other online content | Course home page | Keijo Ruohonen | English |
Prerequisite relations (Requires logging in to POP)
Correspondence of content
There is no equivalence with any other courses
More precise information per implementation
Implementation | Description | Methods of instruction | Implementation |