NMAK14015U Multivariate analysis (MultivAn)
MSc Programme in Statistics
MSc Programme in Mathematics-Economics
Multivariate statistics is about the statistical analysis of data with more than one response variable. The collection of response variables may either have rather low dimension, from 2 to 7, say, or be genuine high dimensional. Analyzing multivariate data can be computationally demanding, and for many of the in practice applied methods there is a strong emphasis on the algorithmic aspects. Such methods includes PCA (principal component analysis), factor analysis, PLS (partial least squares) and PARAFAC (parallel factor analysis). We will describe these methods, and the data situations for which they apply. At the same time we will look for statistical models leading to the listed estimation methods, and see to which degree the multivariate methods can be extended to and embedded in classical statistical models like repeated measurements. As a restriction we exclusive will deal with responses that somehow can be described by a multivariate Gaussian distribution.
Knowledge: To display knowledge of the course content described
above. In particular to relate multivariate methods from
chemometrics to linear mixed models.
Skills: To be able to chose an approriate multivariate method for
analysing data with a multivariate response. To use the statistical
software package R to perform model validation, to estimate
parameters, and to perform model predictions.
Competencies: To be able to discuss possible extensions of the
multivariate methods.
- Category
- Hours
- Exam
- 12
- Lectures
- 24
- Preparation
- 146
- Theory exercises
- 24
- Total
- 206
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- Credit
- 7,5 ECTS
- Type of assessment
- Written assignment, 7 dageOral examination, 30 minutterWritten exercise (weight 1/3): The student will have 7 days to answer an exercise that also will include a practical statistical analysis of a given dataset.
Oral examination (weight 2/3): The oral examination is without preparation. Discussion of the written exercise will be part of the examination. - Aid
- All aids allowed
- Marking scale
- 7-point grading scale
- Censorship form
- No external censorship
Several internal examiners
Criteria for exam assesment
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.
Course information
- Language
- English
- Course code
- NMAK14015U
- Credit
- 7,5 ECTS
- Level
- Full Degree Master
- Duration
- 1 block
- Placement
- Block 2
- Schedule
- B (Mon 8-12 + Tues 13-17 + Fri 8-12)
- Course capacity
- No limit
- Continuing and further education
- Study board
- Study Board of Mathematics and Computer Science
Contracting department
- Department of Mathematical Sciences
Course responsibles
- Bo Markussen (5-6774726677457266796d33707a336970)
Phone: +45 353-20778
Lecturers
Bo Markussen