Duration:
1 Semester | Turnus of offer:
every second year | Credit points:
5 |
Course of studies, specific field and terms: - Master CLS 2023 (optional subject), mathematics, 1st, 2nd, or 3rd semester
- Bachelor CLS 2023 (optional subject), mathematics, 5th or 6th semester
- Bachelor CLS 2016 (optional subject), mathematics, 5th or 6th semester
- Master CLS 2016 (optional subject), mathematics, 1st, 2nd, or 3rd semester
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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
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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
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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.
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Grading through: |
Requires: |
Responsible for this module: Teachers: |
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
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Language: |
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 |
Letzte Änderung: 22.2.2022 |
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