Syllabus for Multivariate Statistical Analysis
Multivariat statistisk teori och metodik
- 7.5 credits
- Course code: 2ST125
- Education cycle: Second cycle
Main field(s) of study and in-depth level:
Explanation of codes
The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:
- G1N: has only upper-secondary level entry requirements
- G1F: has less than 60 credits in first-cycle course/s as entry requirements
- G1E: contains specially designed degree project for Higher Education Diploma
- G2F: has at least 60 credits in first-cycle course/s as entry requirements
- G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
- GXX: in-depth level of the course cannot be classified
- A1N: has only first-cycle course/s as entry requirements
- A1F: has second-cycle course/s as entry requirements
- A1E: contains degree project for Master of Arts/Master of Science (60 credits)
- A2E: contains degree project for Master of Arts/Master of Science (120 credits)
- AXX: in-depth level of the course cannot be classified
- Grading system: Fail (U), Pass (G), Pass with distinction (VG)
- Established: 2020-03-13
- Established by:
- Revised: 2022-10-14
- Revised by: The Department Board
- Applies from: Autumn 2023
120 credits including 90 credits in statistics, or 120 credits including 60 credits in statistics and 30 credits in mathematics and/or computer science. 7,5 credits linear algebra.
- Responsible department: Department of Statistics
After completing the course the student is expected to
- know and be able to use multivariate statistical methods
- know to the underlying theory of multivariate statistical methods
Multivariate data; Basic measures and statistics
Inference for one- and two-means; Profile analysis; Multiple comparisons
Multivariate general linear model: MANOVA and Multivariate regression
Principal components analysis
Canonical correlation analysis
Teaching can be given in the form of lectures, calculation exercises and computer exercises.
The examination takes place partly through a written examination at the end of the course and/or through presentation orally and in written form of compulsory assignments.
The course is included in the Master's programme in statistics.
- Latest syllabus (applies from Autumn 2023)
- Previous syllabus (applies from Autumn 2022)
- Previous syllabus (applies from Autumn 2020)
Applies from: Autumn 2023
Some titles may be available electronically through the University library.
Johnson, Richard Arnold;
Wichern, Dean W.
Applied multivariate statistical analysis
6. ed.: Upper Saddle River, N.J.: Pearson Prentice Hall, cop. 2007