Module MA4944-KP05
Multivariate Statistics (MulStaKP05)
Duration
1 Semester
Turnus of offer
every second year
Credit points
5
Course of studies, specific fields and terms:
- Master CLS 2023, optional subject, mathematics
- Bachelor CLS 2023, optional subject, mathematics
- Bachelor CLS 2016, optional subject, mathematics
- Master CLS 2016, optional subject, mathematics
Classes and lectures:
- Multivariate Statistics (exercise, 1 SWS)
- Multivariate Statistics (lecture, 2 SWS)
Workload:
- 30 hours work on project
- 20 hours exam preparation
- 55 hours private studies
- 45 hours in-classroom work
Contents of teaching:
- Multivariate probability distributions
- Multiple and multivariate regression
- Discriminant analysis and logistic regression
- Cluster analysis with various distance and similarity measures
- Principal component and factor analysis
- Correspondence analysis and multidimensional scaling
- Structural equation models
Qualification-goals/Competencies:
- Students command a broad repertoire of multivariate statistical methods.
- They are able to explain the ideas behind several representative methods.
- They apply these methods by hand and with R packages.
- They analyse problems and choose suitable methods.
- They are able to decide for a better option, e.g. standardization, variance structures, distance measures, factor numbers or rotations.
- They develop multivariate models.
Grading through:
- written exam
Responsible for this module:
Teacher:
- Institute of Medical Biometry and Statistics
- PD Dr. rer. pol. Reinhard Vonthein
- MitarbeiterInnen des Instituts
Literature:
- Fahrmeir, Ludwig; Hamerle, Alfred; Tutz, Gerhard : Multivariate statistische Verfahren ISBN-13 9783110138061
- Johnson, R. J.; Wichern, D. W. : Applied Multivariate Statistical Analysis 5. Ed. Prentice Hall, 2002 - ISBN-13: 000-0131877151
Language:
- offered only in German
Notes:
Admission requirements for taking the module:- None (The competencies of the modules listed under 'Requires' are needed for this module, but are not a formal prerequisite)
Admission requirements for participation in module examination(s):
- Successful completion of homework assignments as specified at the beginning of the semester
Module exam(s):
- MA4944-L1: Multivariate Statistics, written exam, 90 min, 100 % of module grade
Last Updated:
22.02.2022